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市場調查報告書
商品編碼
1544620

第四方物流 (4PL) 市場、機會、成長動力、產業趨勢分析與預測，2024-2032 年

Fourth-Party Logistics (4PL) Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032
出版日期: | 出版商: Global Market Insights Inc. | 英文 270 Pages | 商品交期: 2-3個工作天內

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簡介目錄

在人工智慧 (AI)、機器學習和巨量資料分析等先進技術整合的推動下，第四方物流 (4PL) 市場規模在 2024 年至 2032 年期間將以超過 6.5% 的複合年成長率成長。根據《富比士》報道，自 2017 年以來，全球企業對人工智慧的採用率增加了一倍多，並且繼續以強勁的速度成長，未來幾年有望實現更大的擴張。人工智慧和機器學習使 4PL 供應商能夠提供預測性見解、自動化決策流程並即時最佳化物流營運。巨量資料分析透過提供對供應鏈動態的深入洞察，幫助預測需求、管理庫存和簡化運輸，進一步增強企業的能力。

隨著企業努力提高供應鏈效率，他們開始轉向利用先進技術提供即時分析和預測功能的 4PL 供應商。這些創新使公司能夠預測潛在的中斷、最佳化交付路線並提高整體物流績效。預測洞察有助於更有效地預測需求模式和管理庫存水平，而路線最佳化則可降低運輸成本並縮短交貨時間。這些技術的整合正在重塑各產業的物流策略，提高市場估值。

第四方物流行業根據最終用戶、營運模式、解決方案、模式和區域進行分類。

由於需要高效、整合的物流管理來處理複雜的供應鏈，到 2032 年，製造領域將快速成長。製造商正在利用 4PL 供應商來簡化營運、降低成本並提高供應鏈可視性。這些物流合作夥伴提供涵蓋供應鏈規劃、採購、倉儲和運輸的先進解決方案，使製造商能夠專注於其核心競爭力，同時受益於更高的效率和可擴展性。

到 2032 年，產業創新者細分市場將實現穩定成長，因為 4PL 供應商不僅透過技術進步和創新策略管理供應鏈流程，而且還轉變供應鏈流程。第四方物流 (4PL) 參與者正在利用人工智慧、機器學習和巨量資料分析等技術來提供預測見解、最佳化路線並增強決策能力。透過採用積極主動的物流管理方法，產業創新者正在為效率和有效性設定新的基準，推動 4PL 市場的發展。

2024-2032年歐洲第四方物流業將快速成長。由於需要更大的靈活性、效率和成本效益，歐洲企業擴大轉向第四方物流 (4PL) 供應商來應對供應鏈的複雜性。第四方物流 (4PL) 供應商正在利用其區域專業知識提供量身定做的解決方案，以滿足本地和國際企業的特定需求。此外，對基礎設施和技術的大量投資進一步推動了歐洲 4PL 服務的成長。

目錄

第 1 章：方法與範圍

第 2 章：執行摘要

第 3 章：產業洞察

  • 產業生態系統分析
  • 供應商格局
    • 入庫物流
    • 出庫物流
    • 客戶至供應商的退貨流程
    • 客戶至顧客退貨流程
    • 加值倉儲及配送 (VAWD)
    • 庫存管理和最佳化
  • 利潤率分析
  • 技術和創新格局
  • 專利分析
  • 重要新聞和舉措
  • 監管環境
  • 衝擊力
    • 成長動力
      • 電子商務和零售業的成長
      • 無縫供應鏈的需求
      • 專注科技與數位化
      • 全球化與跨境貿易
    • 產業陷阱與挑戰
      • 對供應鏈的控制有限
      • 對外部合作夥伴的高度依賴
  • 成長潛力分析
  • 波特的分析
  • PESTEL分析

第 4 章：競爭格局

  • 介紹
  • 公司市佔率分析
  • 競爭定位矩陣
  • 戰略展望矩陣

第 5 章：市場估計與預測：按解決方案，2021 - 2032 年

  • 主要趨勢
  • 供應鏈最佳化
  • 運輸管理
  • 庫存管理
  • 倉庫管理
  • 訂單履行
  • 貨運代理
  • 配送管理

第 6 章：市場估計與預測：按營運模式，2021 - 2032 年

  • 主要趨勢
  • 協同加組織
  • 解決方案整合商
  • 產業創新者

第 7 章：市場估計與預測：按模式，2021 - 2032

  • 主要趨勢
  • 空氣
  • 海
  • 鐵路和公路

第 8 章：市場估計與預測：按最終用戶分類，2021 - 2032 年

  • 主要趨勢
  • 食品和飲料
  • 衛生保健
  • 零售
  • 汽車
  • 製造業
  • 其他

第 9 章：市場估計與預測：按地區分類，2021 - 2032 年

  • 主要趨勢
  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 北歐人
    • 歐洲其他地區
  • 亞太地區
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 韓國
    • 東南亞
    • 亞太地區其他地區
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
    • 拉丁美洲其他地區
  • MEA
    • 阿拉伯聯合大公國
    • 南非
    • 沙烏地阿拉伯
    • MEA 的其餘部分

第 10 章：公司簡介

  • Agility Logistics
  • CEVA Logistics
  • DB Schenker
  • DHL Supply Chain
  • DSV Panalpina
  • Expeditors International
  • FedEx Supply Chain
  • Geodis
  • Hellmann Worldwide Logistics
  • Kintetsu World Express
  • Kuehne+Nagel
  • Maersk (A.P. Moller-Maersk)
  • Nippon Express
  • Ryder System
  • Sinotrans
  • TMC, a division of C.H. Robinson
  • Toll Group
  • UPS Supply Chain Solutions
  • XPO Logistics
  • Yusen Logistics
簡介目錄
Product Code: 10155

The Fourth-Party Logistics (4PL) Market Size will grow at over 6.5% CAGR during 2024-2032, driven by the integration of advanced technologies such as artificial intelligence (AI), machine learning, and big data analytics. According to Forbes, the global adoption of AI by enterprises has more than doubled since 2017 and continues to grow at a robust pace, with promising prospects for even greater expansion in the coming years. AI and machine learning enable 4PL providers to offer predictive insights, automate decision-making processes, and optimize logistics operations in real-time. Big data analytics further empowers businesses by providing deep insights into supply chain dynamics, helping to forecast demand, manage inventory, and streamline transportation.

As businesses strive to enhance their supply chain efficiency, they are turning to 4PL providers that leverage advanced technologies to offer real-time analytics and predictive capabilities. These innovations enable companies to anticipate potential disruptions, optimize delivery routes, and improve overall logistics performance. Predictive insights help in forecasting demand patterns and managing inventory levels more effectively, while route optimization reduces transportation costs and improves delivery times. The integration of these technologies is reshaping logistics strategies across various industries, adding to market valuation.

The fourth-party logistics industry is classified based on end-user, operational model, solution, mode, and region.

The manufacturing segment will grow rapidly through 2032, driven by the need for efficient, integrated logistics management to handle complex supply chains. Manufacturers are leveraging 4PL providers to streamline their operations, reduce costs, and enhance supply chain visibility. These logistics partners offer advanced solutions that encompass supply chain planning, procurement, warehousing, and transportation, allowing manufacturers to focus on their core competencies while benefiting from improved efficiency and scalability.

The industry innovator segment will witness steady growth through 2032, as 4PL providers not only manage but also transform supply chain processes through technological advancements and innovative strategies. 4PL players are harnessing technologies such as artificial intelligence, machine learning, and big data analytics to offer predictive insights, optimize routes, and enhance decision-making capabilities. By adopting a proactive approach to logistics management, industry innovators are setting new benchmarks for efficiency and effectiveness, driving the evolution of the 4PL market.

Europe fourth-party logistics industry will witness rapid growth over 2024-2032. European businesses are increasingly turning to 4PL providers to navigate the complexities of the supply chain, driven by the need for greater flexibility, efficiency, and cost-effectiveness. The 4PL providers are capitalizing on their regional expertise to offer tailored solutions that address the specific needs of local and international businesses. Additionally, the significant investments in infrastructure and technology are further fueling the growth of 4PL services in Europe.

Table of Contents

Chapter 1 Methodology and Scope

  • 1.1 Market scope and definition
  • 1.2 Research design
    • 1.2.1 Research approach
    • 1.2.2 Data collection methods
  • 1.3 Base estimates and calculations
    • 1.3.1 Base year calculation
    • 1.3.2 Key trends for market estimation
  • 1.4 Forecast model
  • 1.5 Primary research and validation
    • 1.5.1 Primary sources
    • 1.5.2 Data mining sources

Chapter 2 Executive Summary

  • 2.1 Industry 360° synopsis, 2021 - 2032

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
  • 3.2 Supplier landscape
    • 3.2.1 Inbound logistics
    • 3.2.2 Outbound logistics
    • 3.2.3 Client to supplier return process
    • 3.2.4 Customer to client return process
    • 3.2.5 Value-added Warehousing and Distribution (VAWD)
    • 3.2.6 Inventory management and optimization
  • 3.3 Profit margin analysis
  • 3.4 Technology and innovation landscape
  • 3.5 Patent analysis
  • 3.6 Key news and initiatives
  • 3.7 Regulatory landscape
  • 3.8 Impact forces
    • 3.8.1 Growth drivers
      • 3.8.1.1 Growth of e-commerce and retail
      • 3.8.1.2 Demand for seamless supply chains
      • 3.8.1.3 Focus on technology and digitalization
      • 3.8.1.4 Globalization and cross-border trade
    • 3.8.2 Industry pitfalls and challenges
      • 3.8.2.1 Limited control over supply chain
      • 3.8.2.2 High dependency on external partners
  • 3.9 Growth potential analysis
  • 3.10 Porter's analysis
    • 3.10.1 Supplier power
    • 3.10.2 Buyer power
    • 3.10.3 Threat of new entrants
    • 3.10.4 Threat of substitutes
    • 3.10.5 Industry rivalry
  • 3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

  • 4.1 Introduction
  • 4.2 Company market share analysis
  • 4.3 Competitive positioning matrix
  • 4.4 Strategic outlook matrix

Chapter 5 Market Estimates and Forecast, By Solution, 2021 - 2032 ($Bn)

  • 5.1 Key trends
  • 5.2 Supply chain optimization
  • 5.3 Transportation management
  • 5.4 Inventory management
  • 5.5 Warehouse management
  • 5.6 Order fulfillment
  • 5.7 Freight forwarding
  • 5.8 Distribution management

Chapter 6 Market Estimates and Forecast, By Operational Model, 2021 - 2032 ($Bn)

  • 6.1 Key trends
  • 6.2 Synergy plus organization
  • 6.3 Solution integrator
  • 6.4 Industry innovator

Chapter 7 Market Estimates and Forecast, By Mode, 2021 - 2032 ($Bn)

  • 7.1 Key trends
  • 7.2 Air
  • 7.3 Sea
  • 7.4 Rail and road

Chapter 8 Market Estimates and Forecast, By End User, 2021 - 2032 ($Bn)

  • 8.1 Key trends
  • 8.2 Food and beverage
  • 8.3 Healthcare
  • 8.4 Retail
  • 8.5 Automotive
  • 8.6 Manufacturing
  • 8.7 Others

Chapter 9 Market Estimates and Forecast, By Region, 2021 - 2032 ($Bn)

  • 9.1 Key trends
  • 9.2 North America
    • 9.2.1 U.S.
    • 9.2.2 Canada
  • 9.3 Europe
    • 9.3.1 UK
    • 9.3.2 Germany
    • 9.3.3 France
    • 9.3.4 Italy
    • 9.3.5 Spain
    • 9.3.6 Russia
    • 9.3.7 Nordics
    • 9.3.8 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 India
    • 9.4.3 Japan
    • 9.4.4 Australia
    • 9.4.5 South Korea
    • 9.4.6 Southeast Asia
    • 9.4.7 Rest of Asia Pacific
  • 9.5 Latin America
    • 9.5.1 Brazil
    • 9.5.2 Mexico
    • 9.5.3 Argentina
    • 9.5.4 Rest of Latin America
  • 9.6 MEA
    • 9.6.1 UAE
    • 9.6.2 South Africa
    • 9.6.3 Saudi Arabia
    • 9.6.4 Rest of MEA

Chapter 10 Company Profiles

  • 10.1 Agility Logistics
  • 10.2 CEVA Logistics
  • 10.3 DB Schenker
  • 10.4 DHL Supply Chain
  • 10.5 DSV Panalpina
  • 10.6 Expeditors International
  • 10.7 FedEx Supply Chain
  • 10.8 Geodis
  • 10.9 Hellmann Worldwide Logistics
  • 10.10 Kintetsu World Express
  • 10.11 Kuehne+Nagel
  • 10.12 Maersk (A.P. Moller-Maersk)
  • 10.13 Nippon Express
  • 10.14 Ryder System
  • 10.15 Sinotrans
  • 10.16 TMC, a division of C.H. Robinson
  • 10.17 Toll Group
  • 10.18 UPS Supply Chain Solutions
  • 10.19 XPO Logistics
  • 10.20 Yusen Logistics