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市場調查報告書
商品編碼
1544622
物流市場機器學習、機會、成長動力、產業趨勢分析與預測,2024-2032Machine Learning in Logistics Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032 |
由於對提高營運效率和節省成本的強烈需求,預計 2024 年至 2032 年間,物流市場規模中的機器學習複合年成長率將超過 23%。透過利用機器學習 (ML) 演算法,物流公司可以分析大量資料集來預測需求、完善路線規劃並增強庫存管理。
透過機器學習,物流提供者可以提供精確的交貨估計,即時監控貨運情況,並根據客戶歷史記錄和偏好來客製化服務。蓬勃發展的電子商務產業,加上對快速、可靠的交付的需求不斷成長,加劇了對能夠增強回應能力和敏捷性的機器學習解決方案的需求。例如,2024 年 1 月,勞埃德·李斯特情報公司 (Lloyd List Intelligence) 推出了用於全球商業航運的「空中交通管制」系統,及時提供船舶到達、出發和停泊時間的資料,以緩解供應鏈挑戰。
整個產業分為組件、技術、組織規模、部署模型、應用程式、最終用戶和區域。
從組成部分來看,服務領域的機器學習在物流市場規模中預計將在 2024 年至 2032 年期間出現顯著成長,因為它在物流領域實施、管理和最佳化機器學習解決方案方面發揮關鍵作用。諮詢、系統整合和管理等服務對於企業熟練實施機器學習、客製化解決方案並將其與現有系統整合至關重要。
預計到 2032 年,車隊管理領域的機器學習物流市場價值將大幅成長。機器學習演算法分析來自各種來源(例如 GPS、遠端資訊處理和駕駛員行為)的資料,以增強路線規劃、監控車輛性能並預測維護需求。
在經濟快速發展、電子商務蓬勃發展以及對供應鏈完善的關注的推動下,預計到 2032 年,亞太地區機器學習在物流行業的規模將大幅成長。隨著城市化和工業成長的不斷發展,亞太地區國家擴大轉向先進的物流解決方案,以熟練地管理該地區錯綜複雜的供應鏈和大量貨物。
Machine learning in logistics market size is anticipated to witness over 23% CAGR between 2024 and 2032 led by strong demand for improved operational efficiency and cost savings. By leveraging machine learning (ML) algorithms, logistics firms can analyze extensive data sets to forecast demand, refine route planning, and enhance inventory management.
With machine learning, logistics providers can deliver precise delivery estimates, monitor shipments in real-time, and customize services based on customer history and preferences. The booming e-commerce sector, coupled with rising demands for swift and reliable deliveries, intensifies the need for ML solutions that bolster responsiveness and agility. For example, in January 2024, Lloyd List Intelligence unveiled an 'air traffic control' system for global commercial shipping, offering timely data on vessel arrivals, departures, and berth times to mitigate supply chain challenges.
The overall industry is divided into component, technique, organization size, deployment model, application, end user, and region.
Based on component, the machine learning in logistics market size from the services segment is slated to witness significant growth during 2024-2032 due to its critical role in implementing, managing, and optimizing ML solutions within the logistics sector. Services like consulting, system integration, and management are vital for firms to adeptly implement machine learning, customize solutions, and integrate them with pre-existing systems.
Machine learning in logistics market value from the fleet management segment will foresee considerable growth up to 2032. This is driven by the need for harnessing advanced analytics to optimize vehicle operations and improve overall efficiency. ML algorithms analyze data from various sources, such as GPS, telematics, and driver behavior, to enhance route planning, monitor vehicle performance, and predict maintenance needs.
Asia Pacific machine learning in logistics industry size is anticipated to witness substantial growth through 2032, fueled by swift economic progress, surging e-commerce, and a focus on supply chain refinement. With urbanization and industrial growth on the rise, APAC nations are increasingly turning to advanced logistics solutions to adeptly manage intricate supply chains and high goods volumes in the region.