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1363526

供應鏈數位孿生市場規模、佔有率、趨勢分析報告：按組件、按部署模式、按公司規模、按行業、按地區、細分市場趨勢，2023-2030 年

Supply Chain Digital Twin Market Size, Share & Trends Analysis Report By Component, By Deployment Mode (On-premise, Cloud), By Enterprise Size, By Industry Vertical, By Region, And Segment Forecasts, 2023 - 2030
出版日期: | 出版商: Grand View Research | 英文 110 Pages | 商品交期: 2-10個工作天內

價格

供應鏈數位孿生市場成長與趨勢：

Grand View Research, Inc.最新報告顯示，到2030年，全球供應鏈數位孿生市場規模預計將達到59.8億美元，2023年至2030年年複合成長率為12.0%。

數位孿生的採用是由行業的快速成長和對最尖端科技的需求所推動的。該技術透過提供整個供應鏈的完整即時影像，實現更好的監控、分析和營運最佳化。

數位孿生是創建整個供應鏈或其中特定組件的數位副本。該副本包括實體資產，例如製造設施、儲存設施、運輸車輛、流程、資料流以及不同結構要素之間的關係。此外，數位孿生還包含物聯網設備、感測器和其他資料來源。這些設備在供應鏈的各個點即時收集溫度、濕度、位置和生產參數。該資訊被輸入數位孿生以實現動態和準確的模擬。

意外停工給工業製造商造成了嚴重的干擾和財務負擔，甚至在疫情爆發之前，每週損失的時間就超過 15 個小時，年度損失的損失超過 500 億美元。這些中斷的很大一部分（大約一半）是由於設備故障造成的。為了應對這些挑戰，一種稱為預測性維護的策略已成為一種引人注目的方法，該策略可以預測故障並搶先修復故障。實施數位孿生有望顯著節省成本並提高生產力，使製造商和物流提供者受益。

數位孿生可以即時洞察實體物件的狀況，是預測性維護的完美解決方案。例如，2022 年，卡夫亨氏與微軟合作，為北美所有 34 個製造廠開發數位位孿生。其主要目標之一是減少每個站點的機械停機時間。

除了綜合倉庫之外，數位孿生還可以有效部署到較小的個別資產。先進的物流公司和設備服務提供者正在創建機器人、卡車、工具等的數位複製品。這種模擬方法可以持續監控其狀況並識別需要及時關注以避免故障的磨損。採用數位孿生來促進預測性維護為物流提供者帶來了顯著的好處。這不僅提高了營運吞吐量，還顯著降低了營運支出。

供應鏈數位孿生市場報告亮點

  • 按組成部分來看，硬體細分市場在整個市場中佔據主導地位，2022 年市場佔有率為 42.0%。該細分市場預計將由現實世界資料的收集、傳輸和處理來驅動，以產生準確和動態的虛擬表示。
  • 按部署型態，本地部署模型主導了整個市場，2022 年市場佔有率為 52.1%。本地部署使公司能夠完全控制資料，並能夠實施安全措施來保護敏感的供應鏈資訊。
  • 根據公司規模，預計2023年至2030年大型企業細分市場的年複合成長率將超過12.5%。大型企業可以使用供應鏈數位孿生來提高整個供應鏈的業務效率、降低成本並改善決策。
  • 按行業分類，在即時需求波動、生產計畫和考慮到銷售線索的存量基準最佳化的推動下，汽車領域預計將在預測期內實現強勁成長，年複合成長率接近 13.3%。
  • 北美在該行業佔據主導地位，2022 年佔全球銷售額的 29.3% 以上。該地區擁有許多領先的科技公司、研究機構和大學，它們正在積極開發和推進供應鏈數位孿生技術。

目錄

第1章 調查方法和範圍

第2章 執行摘要

第3章 市場變數、趨勢與範圍預測

  • 市場體系預測
  • 供應鏈數位孿生市場-價值鏈分析
  • 供應鏈數位孿生市場動態
  • 產業分析-波特五力分析
  • 產業分析-PESTEL分析
  • COVID-19感染疾病的影響分析

第4章 供應鏈數位孿生市場、組件預測

  • 供應鏈數位孿生市場，按成分分析和市場佔有率，2022 年和 2030 年
  • 硬體
  • 軟體
  • 服務

第5章 供應鏈數位市場、部署模式預測

  • 供應鏈數位位孿生市場，按部署模式分析和市場佔有率，2022 年和 2030 年
  • 本地
  • 雲

第6章 供應鏈數位孿生市場、企業規模預測

  • 供應鏈數位位孿生市場，按公司規模分析和市場佔有率，2022 年和 2030 年
  • 主要企業
  • 中小企業

第7章 供應鏈數位孿生市場、產業預測

  • 2022 年和 2030 年供應鏈數位孿生市場、產業分析和市場佔有率
  • 製造業
  • 汽車
  • 航太和國防
  • 零售
  • 藥品
  • 消費品
  • 其他

第8章 供應鏈數位孿生市場：依地區估算及趨勢分析

  • 2022 年及 2030 年供應鏈數位孿生市場佔有率（按地區）
  • 北美洲
    • 按組成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司規模分類，2017-2030
    • 按行業分類，2017-2030
    • 美國
    • 加拿大
  • 歐洲
    • 按組成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司規模分類，2017-2030
    • 按行業分類，2017-2030
    • 德國
    • 英國
    • 法國
  • 亞太地區
    • 按組成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司規模分類，2017-2030
    • 按行業分類，2017-2030
    • 中國
    • 日本
    • 印度
  • 拉丁美洲
    • 按組成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司規模分類，2017-2030
    • 按行業分類，2017-2030
    • 巴西
    • 墨西哥
  • 中東和非洲
    • 按組成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司規模分類，2017-2030
    • 按行業分類，2017-2030
    • 阿拉伯聯合大公國 (UAE)
    • 沙烏地阿拉伯王國 (KSA)
    • 南非

第9章 供應鏈數位孿生市場競爭形勢

  • 主要市場參與企業
    • IBM
    • Oracle
    • SAP
    • Dassault Systemes
    • AVEVA
    • Siemens Digital Industries Software
    • Kinaxis
    • The AnyLogic Company
    • Simio
    • Logivations
  • 2022年主要企業市場佔有率分析
  • 2022 年公司分類/定位分析
  • 策略規劃
    • 擴張
    • 併購
    • 夥伴關係與協作
    • 產品/服務發布
    • 其他
Product Code: GVR-4-68040-128-5

Supply Chain Digital Twin Market Growth & Trends:

The global supply chain digital twin market size is expected to reach USD 5.98 billion by 2030, registering a CAGR of 12.0% from 2023 to 2030, according to a new report by Grand View Research, Inc.. Digital twin adoption has been fueled by the industry's rapid growth and the demand for cutting-edge technology. This technology enables better monitoring, analysis, and operation optimization by providing a complete and real-time picture of the whole supply chain.

A digital twin is the creation of a digital replica of the complete supply chain or certain components within it. This replica contains physical assets such as manufacturing facilities, storage facilities, transportation vehicles, processes, data flows, and relationships between different pieces. Furthermore, the digital twin incorporates IoT devices, sensors, and other data sources. Temperature, humidity, location, and production parameters are all collected in real time by these devices at various points in the supply chain. This information is then input into the digital twin, which allows for a dynamic and accurate simulation.

Unforeseen operational halts pose significant disruptions and financial burdens for industrial manufacturers, amounting to more than 15 hours of lost time per week and exceeding USD 50 billion annually, even before the pandemic. A substantial portion of these interruptions, nearly half, stem from equipment malfunctions. To counteract these challenges, the strategy of predictive maintenance, involving the anticipation and preemptive repair of assets before they malfunction, has emerged as a compelling approach. Its implementation promises substantial cost reductions and heightened productivity, benefiting both manufacturers and logistics providers.

The potency of digital twins in furnishing real-time insights into the status of physical objects positions them as an optimal solution for predictive maintenance. For instance, in 2022, Kraft Heinz joined forces with Microsoft to develop digital twins for all 34 manufacturing facilities in North America. Among the primary aims was the curtailment of mechanical downtime across each establishment.

Beyond just comprehensive warehouses, digital twins can also be effectively deployed for individual assets, even on a smaller scale. Forward-thinking logistics entities and equipment service providers are crafting digital replicas of items such as singular robots, trucks, and tools. This emulation approach enables consistent monitoring of their conditions, identifying wear and tear that necessitates timely attention to avert breakdowns. Employing digital twins to facilitate predictive maintenance yields substantial benefits for logistics providers, including the potential to diminish reactive maintenance by around 40% within a given year. This not only amplifies operational throughput but also substantially reduces operational expenditure.

Supply Chain Digital Twin Market Report Highlights:

  • Based on component, the hardware segment dominated the overall market, accounting for a market share of 42.0% in 2022. The segment is expected to be driven by the gathering, transfer, and processing of real-world data to produce accurate and dynamic virtual representations
  • Based on deployment mode, the on-premise segment dominated the overall market, accounting for a market share of 52.1% in 2022. With on-premises implementation, the firm keeps full control of its data and can install its security measures to protect sensitive supply chain information
  • Based on enterprise size, the large enterprises segment is anticipated to grow at a CAGR of over 12.5% from 2023 to 2030. Large corporations can use supply chain digital twins to improve operational efficiency, lower costs, and improve decision-making across the whole supply chain
  • Based on industrial vertical, the automotive segment is anticipated to witness strong growth with a CAGR of nearly 13.3% over the forecast period, owing to the optimization of inventory levels by taking into account real-time demand variations, production plans, and lead
  • North America dominated the industry, contributing to over 29.3% of the global revenue in 2022. The region is home to many leading technology companies, research institutions, and universities that have been actively developing and advancing digital twin technology for supply chain

Table of Contents

Chapter 1. Methodology and Scope

  • 1.1. Market Segmentation & Scope
  • 1.2. Market Definitions
  • 1.3. Information Procurement
    • 1.3.1. Information analysis
    • 1.3.2. Market formulation & data visualization
    • 1.3.3. Data validation & publishing
  • 1.4. Research Scope and Assumptions
    • 1.4.1. List of Data Sources

Chapter 2. Executive Summary

  • 2.1. Market Summary
  • 2.2. Market Snapshot
  • 2.3. Segment Snapshot
  • 2.4. Competitive Landscape Snapshot

Chapter 3. Market Variables, Trends, & Scope Outlook

  • 3.1. Market Lineage Outlook
  • 3.2. Supply Chain Digital Twin Market - Value Chain Analysis
  • 3.3. Supply Chain Digital Twin Market Dynamics
    • 3.3.1. Market Driver Analysis
    • 3.3.2. Market Restraint Analysis
    • 3.3.3. Market Opportunity Analysis
  • 3.4. Industry Analysis - Porter's Five Forces Analysis
    • 3.4.1. Supplier power
    • 3.4.2. Buyer power
    • 3.4.3. Substitution threat
    • 3.4.4. Threat from new entrant
    • 3.4.5. Competitive rivalry
  • 3.5. Industry Analysis - PESTEL Analysis
    • 3.5.1. Political landscape
    • 3.5.2. Economic landscape
    • 3.5.3. Social landscape
    • 3.5.4. Technology landscape
    • 3.5.5. Environmental landscape
    • 3.5.6. Legal landscape
  • 3.6. COVID-19 Impact Analysis

Chapter 4. Supply Chain Digital Twin Market Component Outlook

  • 4.1. Supply Chain Digital Twin market, By Component Analysis & Market Share, 2022 & 2030
  • 4.2. Hardware
    • 4.2.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 4.2.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 4.3. Software
    • 4.3.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 4.3.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 4.4. Services
    • 4.4.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 4.4.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)

Chapter 5. Supply Chain Digital Twin Market Deployment Mode Outlook

  • 5.1. Supply Chain Digital Twin market, By Deployment Mode Analysis & Market Share, 2022 & 2030
  • 5.2. On-premise
    • 5.2.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 5.2.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 5.3. Cloud
    • 5.3.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 5.3.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)

Chapter 6. Supply Chain Digital Twin Market Enterprise Size Outlook

  • 6.1. Supply Chain Digital Twin market, By Enterprise Size Analysis & Market Share, 2022 & 2030
  • 6.2. Large Enterprise
    • 6.2.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 6.2.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 6.3. Small and medium enterprises
    • 6.3.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 6.3.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)

Chapter 7. Supply Chain Digital Twin Market Industry Vertical Outlook

  • 7.1. Supply Chain Digital Twin market, By Industry Vertical Analysis & Market Share, 2022 & 2030
  • 7.2. Manufacturing
    • 7.2.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.2.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.3. Automotive
    • 7.3.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.3.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.4. Aerospace & Defense
    • 7.4.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.4.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.5. Retail
    • 7.5.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.5.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.6. Pharmaceuticals
    • 7.6.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.6.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.7. Consumer Goods
    • 7.7.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.7.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.8. Others
    • 7.8.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.8.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)

Chapter 8. Supply Chain Digital Twin market: Regional Estimates & Trend Analysis

  • 8.1. Supply Chain Digital Twin Market Share by Region, 2022 & 2030
  • 8.2. North America
    • 8.2.1. Market estimates and forecasts, 2017 - 2030
    • 8.2.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.2.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.2.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.2.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.2.6. U.S.
      • 8.2.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.2.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.2.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.2.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.2.7. Canada
      • 8.2.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.2.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.2.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.2.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
  • 8.3. Europe
    • 8.3.1. Market estimates and forecasts, 2017 - 2030
    • 8.3.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.3.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.3.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.3.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.3.6. Germany
      • 8.3.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.3.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.3.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.3.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.3.7. UK
      • 8.3.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.3.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.3.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.3.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.3.8. France
      • 8.3.8.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.3.8.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.3.8.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.3.8.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
  • 8.4. Asia-Pacific
    • 8.4.1. Market estimates and forecasts, 2017 - 2030
    • 8.4.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.4.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.4.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.4.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.4.6. China
      • 8.4.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.4.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.4.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.4.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.4.7. Japan
      • 8.4.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.4.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.4.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.4.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.4.8. India
      • 8.4.8.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.4.8.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.4.8.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.4.8.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
  • 8.5. Latin America
    • 8.5.1. Market estimates and forecasts, 2017 - 2030
    • 8.5.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.5.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.5.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.5.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.5.6. Brazil
      • 8.5.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.5.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.5.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.5.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.5.7. Mexico
      • 8.5.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.5.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.5.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.5.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
  • 8.6. Middle East & Africa
    • 8.6.1. Market estimates and forecasts, 2017 - 2030
    • 8.6.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.6.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.6.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.6.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.6.6. United Arab Emirates (UAE)
      • 8.6.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.6.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.6.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.6.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.6.7. Kingdom of Saudi Arabia(KSA)
      • 8.6.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.6.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.6.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.6.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.6.8. South Africa
      • 8.6.8.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.6.8.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.6.8.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.6.8.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)

Chapter 9. Supply Chain Digital Twin Market Competitive Landscape

  • 9.1. Key Market Participants
    • 9.1.1. IBM
    • 9.1.2. Oracle
    • 9.1.3. SAP
    • 9.1.4. Dassault Systemes
    • 9.1.5. AVEVA
    • 9.1.6. Siemens Digital Industries Software
    • 9.1.7. Kinaxis
    • 9.1.8. The AnyLogic Company
    • 9.1.9. Simio
    • 9.1.10. Logivations
  • 9.2. Key Company Market Share Analysis, 2022
  • 9.3. Company Categorization/Position Analysis, 2022
  • 9.4. Strategic Mapping
    • 9.4.1. Expansion
    • 9.4.2. Mergers & Acquisition
    • 9.4.3. Partnership & Collaborations
    • 9.4.4. Product/service launch
    • 9.4.5. Others 

List of Tables

  • Table 1 Supply Chain Digital Twin market, by component, 2017 - 2030 (USD Million)
  • Table 2 Supply Chain Digital Twin market, by deployment mode, 2017 - 2030 (USD Million)
  • Table 3 Supply Chain Digital Twin market, by enterprise size, 2017 - 2030 (USD Million)
  • Table 4 Supply Chain Digital Twin market, by industry vertical, 2017 - 2030 (USD Million)
  • Table 5 Participant's Overview
  • Table 6 Financial Performance
  • Table 7 Product benchmarking
  • Table 8 Company Heat Map Analysis
  • Table 9 Key Companies undergoing expansions.
  • Table 10 Key Companies involved in M&As
  • Table 11 Key Companies undergoing partnerships & collaborations.

List of Figures

  • Fig. 1 Supply Chain Digital Twin Market Segmentation
  • Fig. 2 Supply Chain Digital Twin Market - Regional Scope
  • Fig. 3 Information Procurement
  • Fig. 4 Data Analysis Models
  • Fig. 5 Market Formulation and Validation
  • Fig. 6 Data Validating & Publishing
  • Fig. 7 Supply Chain Digital Twin Market Snapshot, 2022 & 2030
  • Fig. 8 Supply Chain Digital Twin Market -Segment Snapshot, by Enterprise Size & Industry Vertical, 2022 & 2030
  • Fig. 9 Supply Chain Digital Twin Market - Competitive Landscape Snapshot
  • Fig. 10 Supply Chain Digital Twin Market Value, 2022 (USD Billion)
  • Fig. 11 Value chain analysis
  • Fig. 12 Supply Chain Digital Twin Market Trends
  • Fig. 13 Supply Chain Digital Twin market - Porter's five forces analysis
  • Fig. 14 Supply Chain Digital Twin market - PESTEL analysis
  • Fig. 15 Supply Chain Digital Twin Market, by Component: Key Takeaways
  • Fig. 16 Supply Chain Digital Twin Market, by Component: Market Share, 2022 & 2030
  • Fig. 17 Supply Chain Digital Twin Market Estimates and Forecasts, by Hardware, 2017 - 2030 (USD Million)
  • Fig. 18 Supply Chain Digital Twin Market Estimates and Forecasts, by Software, 2017 - 2030 (USD Million)
  • Fig. 19 Supply Chain Digital Twin Market Estimates and Forecasts, by Services, 2017 - 2030 (USD Million)
  • Fig. 20 Supply Chain Digital Twin Market, by Deployment Mode: Key Takeaways
  • Fig. 21 Supply Chain Digital Twin Market, by Deployment Mode: Market Share, 2022 & 2030
  • Fig. 22 Supply Chain Digital Twin Market Estimates and Forecasts, by On-premise, 2017 - 2030 (USD Million)
  • Fig. 23 Supply Chain Digital Twin Market Estimates and Forecasts, by Cloud, 2017 - 2030 (USD Million)
  • Fig. 24 Supply Chain Digital Twin Market, by Enterprise Size: Key Takeaways
  • Fig. 25 Supply Chain Digital Twin Market, by Enterprise Size: Market Share, 2022 & 2030
  • Fig. 26 Supply Chain Digital Twin Market Estimates and Forecasts, by Large Enterprises, 2017 - 2030 (USD Million)
  • Fig. 27 Supply Chain Digital Twin Market Estimates and Forecasts, by Small and medium enterprises, 2017 - 2030 (USD Million)
  • Fig. 28 Supply Chain Digital Twin Market, by Industry Vertical: Key Takeaways
  • Fig. 29 Supply Chain Digital Twin Market, by Industry Vertical: Market Share, 2022 & 2030
  • Fig. 30 Supply Chain Digital Twin Market Estimates and Forecasts, By Manufacturing, 2017 - 2030 (USD Million)
  • Fig. 31 Supply Chain Digital Twin Market Estimates and Forecasts, by Automotive, 2017 - 2030 (USD Million)
  • Fig. 32 Supply Chain Digital Twin Market Estimates and Forecasts, by Aerospace & Defense, 2017 - 2030 (USD Million)
  • Fig. 33 Supply Chain Digital Twin Market Estimates and Forecasts, by Retail, 2017 - 2030 (USD Million)
  • Fig. 34 Supply Chain Digital Twin Market Estimates and Forecasts, By Pharmaceuticals, 2017 - 2030 (USD Million)
  • Fig. 35 Supply Chain Digital Twin Market Estimates and Forecasts, by Consumer Goods, 2017 - 2030 (USD Million)
  • Fig. 36 Supply Chain Digital Twin Market Estimates and Forecasts, by Others, 2017 - 2030 (USD Million)
  • Fig. 37 Supply Chain Digital Twin Market revenue- by region, 2022 & 2030 (USD Million)
  • Fig. 38 Regional Marketplace (North America & Europe)- Key Takeaways
  • Fig. 39 Regional Marketplace (Asia Pacific and Latin America) - Key Takeaways
  • Fig. 40 Regional Marketplace (MEA)- Key Takeaways
  • Fig. 41 North America Supply Chain Digital Twin Market estimates & forecast, 2017 - 2030 (USD Million)
  • Fig. 42 U.S. Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 43 Canada Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 44 Europe Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 45 UK Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 46 Germany Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 47 France Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 48 Asia Pacific Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 49 China Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 50 India Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 51 Japan Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 52 Latin America Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 53 Brazil Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 54 Mexico Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 55 Middle East & Africa (MEA) Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 56 United Arab Emirates (UAE) Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 57 Kingdom of Saudi Arabia (KSA) Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 58 South Africa Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 59 Key Company Categorization
  • Fig. 60 Company Market Share Analysis, 2022
  • Fig. 61 Strategic framework