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市場調查報告書
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1691790

零售邊緣運算市場 - 全球產業規模、佔有率、趨勢、機會和預測，按組件、按應用、按組織規模、按地區和競爭進行細分，2020-2030 年預測

Retail Edge Computing Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Application, By Organization Size, By Region & Competition, 2020-2030F
出版日期: | 出版商: TechSci Research | 英文 185 Pages | 商品交期: 2-3個工作天內

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簡介目錄

2024 年全球零售邊緣運算市場價值為 48.7 億美元，預計到 2030 年將達到 151.9 億美元，複合年成長率為 20.88%。零售邊緣運算是指在更靠近資料產生地點（例如零售店或配送中心現場）處理資料的做法，而不是僅依賴遠端資料中心或雲端平台。該技術利用感測器、攝影機和物聯網 (IoT) 系統等邊緣設備即時收集、處理和分析資料，使零售商能夠更快地做出數據驅動的決策。零售業擴大採用邊緣運算，因為它可以更快地響應客戶需求、更好地管理庫存、提供個人化的購物體驗並提高營運效率。例如，店內攝影機的即時分析可以最佳化商店佈局，預測消費者行為，甚至透過先進的安全系統減少竊盜。邊緣運算透過提供有關庫存水準和客戶偏好的近乎即時的回饋來增強供應鏈管理。

市場概況
預測期 2026-2030
2024 年市場規模 48.7 億美元
2030 年市場規模 151.9 億美元
2025-2030 年複合年成長率 20.88％
成長最快的領域 中小企業
最大的市場 北美洲

由於幾個關鍵促進因素，零售邊緣運算市場預計將大幅成長。由於客戶對即時和客製化服務的期望，對超個人化購物體驗的需求日益成長，推動零售商採用能夠提供即時洞察的技術。隨著零售環境中物聯網設備和感測器的數量不斷增加，對分散式運算的需求也隨之成長，以處理這些設備產生的大量資料。 5G網路的持續擴張進一步加速了這一轉變，因為5G實現了高速、低延遲通訊，使得邊緣運算在處理即時資料方面更加有效。全通路零售的興起，即消費者透過實體店和數位平台與品牌互動，需要邊緣運算能夠支援的無縫、反應迅速的系統。由於零售商力求確保高效、安全地處理客戶資料，安全問題和減少處理交易時資料延遲的需求也在邊緣運算的採用中發揮了一定作用。智慧貨架、自動結帳和個人化促銷等自動化在零售營運中的重要性日益增加，是推動市場成長的另一個因素。由於邊緣運算能夠實現更快的本地處理，零售商可以簡化營運並增強客戶參與度，從而在擁擠的市場中獲得更激烈的競爭優勢。因此，在技術進步、營運效率需求以及個人化、即時客戶體驗的推動下，零售邊緣運算市場將快速成長。

主要市場促進因素

即時數據處理和決策的需求

主要市場挑戰

與現有基礎設施整合的複雜性

主要市場趨勢

邊緣人工智慧和機器學習的採用率不斷提高

目錄

第 1 章：解決方案概述

  • 市場定義
  • 市場範圍
    • 覆蓋市場
    • 考慮學習年限
    • 主要市場區隔

第 2 章：研究方法

第 3 章：執行摘要

第 4 章：顧客之聲

第5章：全球零售邊緣運算市場概覽

第6章：全球零售邊緣運算市場展望

  • 市場規模和預測
    • 按價值
  • 市場佔有率和預測
    • 按組件（硬體、軟體、服務）
    • 按應用（智慧城市、工業物聯網、遠端監控、內容交付、擴增實境、虛擬實境、其他）
    • 依組織規模（中小型企業、大型企業）
    • 按地區（北美、歐洲、南美、中東和非洲、亞太地區）
  • 按公司分類（2024）
  • 市場地圖

第7章：北美零售邊緣運算市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 北美：國家分析
    • 加拿大
    • 墨西哥

第 8 章：歐洲零售邊緣運算市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 歐洲：國家分析
    • 法國
    • 英國
    • 義大利
    • 西班牙
    • 比利時

第9章：亞太零售邊緣運算市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 亞太地區：國家分析
    • 印度
    • 日本
    • 韓國
    • 澳洲
    • 印尼
    • 越南

第 10 章：南美洲零售邊緣運算市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 南美洲：國家分析
    • 哥倫比亞
    • 阿根廷
    • 智利

第 11 章：中東和非洲零售邊緣運算市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 中東和非洲：國家分析
    • 阿拉伯聯合大公國
    • 南非
    • 土耳其
    • 以色列

第 12 章：市場動態

  • 驅動程式
  • 挑戰

第 13 章：市場趨勢與發展

第 14 章：公司簡介

  • Amazon.com, Inc.
  • Microsoft Corporation
  • IBM Corporation
  • Intel Corporation
  • Cisco Systems, Inc.
  • Hewlett Packard Enterprise Company
  • NVIDIA Corporation
  • Google LLC
  • Oracle Corporation
  • Qualcomm Incorporated

第 15 章：策略建議

第16章調查會社について,免責事項

簡介目錄
Product Code: 27516

The Global Retail Edge Computing Market was valued at USD 4.87 billion in 2024 and is expected to reach USD 15.19 billion by 2030 with a CAGR of 20.88% through 2030. Retail Edge Computing refers to the practice of processing data closer to the location where it is generated, such as on-site at retail stores or distribution centers, rather than relying solely on distant data centers or cloud platforms. This technology leverages edge devices like sensors, cameras, and IoT (Internet of Things) systems to collect, process, and analyze data in real time, enabling retailers to make faster, data-driven decisions. The retail sector has been increasingly adopting edge computing as it allows for quicker responses to customer needs, better inventory management, personalized shopping experiences, and improved operational efficiency. For example, real-time analytics from in-store cameras can optimize store layouts, predict consumer behavior, and even reduce theft through advanced security systems. Edge computing enhances supply chain management by providing near-instantaneous feedback on inventory levels and customer preferences.

Market Overview
Forecast Period2026-2030
Market Size 2024USD 4.87 Billion
Market Size 2030USD 15.19 Billion
CAGR 2025-203020.88%
Fastest Growing SegmentSmall & Medium Enterprises
Largest MarketNorth America

The market for retail edge computing is expected to rise significantly due to several key drivers. The growing demand for hyper-personalized shopping experiences, driven by customer expectations for instant and tailored services, is pushing retailers to adopt technologies that can provide real-time insights. As the number of IoT devices and sensors in retail environments continues to increase, the need for decentralized computing grows to handle the massive volume of data these devices generate. The ongoing expansion of 5G networks further accelerates this shift, as 5G enables high-speed, low-latency communication, making edge computing more effective in handling real-time data processing. The rise of omnichannel retail, where consumers interact with brands through both physical stores and digital platforms, demands seamless and responsive systems that edge computing can support. Security concerns and the need for reducing data latency in processing transactions also play a role in the adoption of edge computing, as retailers seek to ensure customer data is handled efficiently and securely. The increasing importance of automation in retail operations, such as smart shelves, automated checkout, and personalized promotions, is another factor driving the market's growth. As edge computing enables faster, local processing, retailers can streamline operations and enhance customer engagement, leading to more competitive advantages in a crowded market. Therefore, the retail edge computing market is poised to grow rapidly, driven by advancements in technology, the need for operational efficiency, and the push for personalized, real-time customer experiences.

Key Market Drivers

Demand for Real-Time Data Processing and Decision Making

One of the primary drivers of the retail edge computing market is the increasing demand for real-time data processing and decision making within retail environments. The modern retail landscape is becoming increasingly data-driven, with retailers collecting vast amounts of information from in-store sensors, cameras, point-of-sale systems, and online interactions. These data points include customer behavior, inventory levels, and transaction details. For retail businesses, the ability to process this information as it is generated, without having to send it to a centralized cloud or data center, has become a critical factor in staying competitive. Retailers are under constant pressure to improve customer experiences, optimize operations, and stay ahead of market trends. Real-time data processing allows them to gain immediate insights into their operations, whether it is for analyzing customer foot traffic, adjusting pricing, or making stock replenishment decisions. Edge computing enables data to be processed closer to the point of origin, reducing latency and enabling quicker decision-making, which is especially crucial during peak hours or sales events. For instance, by leveraging real-time data at the edge, a retailer can adjust promotions, manage store layouts, and even optimize staff allocation instantly based on customer behavior patterns, thereby enhancing operational efficiency and improving customer experience. This ability to make informed decisions promptly is a major factor driving the retail edge computing market's growth. By the end of 2025, it is estimated that 80% of all enterprise data will need to be processed in real-time or near real-time to drive critical decision-making.

Key Market Challenges

Complexity of Integration with Existing Infrastructure

One of the primary challenges for the retail edge computing market is the complexity of integrating edge computing solutions with existing retail infrastructure. Many retailers, particularly legacy businesses, already have established systems in place for their operations, such as centralized data centers, cloud-based applications, and traditional point-of-sale systems. Implementing edge computing requires significant changes to this infrastructure, which can be costly, time-consuming, and technically challenging. Retailers must ensure that their edge computing solutions are seamlessly integrated with these legacy systems to maintain smooth operations and avoid disruptions. This can involve substantial investments in both hardware and software, as well as training personnel to manage and operate new systems. Many edge computing solutions require specialized hardware, such as local data processing units, sensors, or specialized network equipment, which may not be compatible with older retail technologies. Integrating such diverse systems can lead to compatibility issues, data silos, or inefficiencies that hinder the desired performance improvements. The process of integration may involve significant customization to align with the specific needs of a retail business. Retailers must work closely with technology vendors and service providers to ensure that edge computing solutions are tailored to their particular operational requirements, which can increase project timelines and costs. For businesses with a wide range of store formats or a diverse product offering, integrating edge computing at scale can be particularly challenging. A lack of standardized solutions or processes across different retail environments can create inconsistencies in performance and operational challenges, delaying the expected benefits of edge computing. Thus, retailers face considerable challenges in ensuring that edge computing solutions can be effectively incorporated into their existing infrastructure while maintaining operational continuity.

Key Market Trends

Increased Adoption of Artificial Intelligence and Machine Learning at the Edge

One of the significant trends in the retail edge computing market is the increasing integration of artificial intelligence and machine learning technologies directly at the edge. Traditionally, artificial intelligence and machine learning models required heavy processing power in centralized cloud environments, resulting in latency and bandwidth challenges. However, with the advancement of edge computing technologies, retailers are now able to deploy these advanced algorithms at the edge, closer to where data is generated. This enables real-time analysis of customer behavior, inventory management, and store operations. For example, edge devices equipped with artificial intelligence can instantly analyze video feeds from in-store cameras to recognize customer actions, detect patterns, and even predict future purchasing behavior. Retailers can leverage this data to offer personalized promotions, optimize store layouts, or detect shoplifting in real-time. Machine learning algorithms can be used to predict inventory needs based on in-store data, reducing stockouts and overstocking. The ability to run these sophisticated models locally ensures quicker response times and minimizes the need for constant cloud communication, which enhances overall system efficiency. The growing reliance on artificial intelligence and machine learning at the edge is transforming how retailers operate, providing them with enhanced insights and decision-making capabilities that drive business success.

Key Market Players

  • Amazon.com, Inc.
  • Microsoft Corporation
  • IBM Corporation
  • Intel Corporation
  • Cisco Systems, Inc.
  • Hewlett Packard Enterprise Company
  • NVIDIA Corporation
  • Google LLC
  • Oracle Corporation
  • Qualcomm Incorporated

Report Scope:

In this report, the Global Retail Edge Computing Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Retail Edge Computing Market, By Component:

  • Hardware
  • Software
  • Services

Retail Edge Computing Market, By Application:

  • Smart Cities
  • Industrial Internet of Things
  • Remote Monitoring
  • Content Delivery
  • Augmented Reality
  • Virtual Reality
  • Others

Retail Edge Computing Market, By Organization Size:

  • Small & Medium Enterprises
  • Large Enterprises

Retail Edge Computing Market, By Region:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • France
    • United Kingdom
    • Italy
    • Spain
    • Belgium
  • Asia Pacific
    • China
    • India
    • Japan
    • South Korea
    • Australia
    • Indonesia
    • Vietnam
  • South America
    • Brazil
    • Colombia
    • Argentina
    • Chile
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • South Africa
    • Turkey
    • Israel

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Retail Edge Computing Market.

Available Customizations:

Global Retail Edge Computing Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Solution Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Formulation of the Scope
  • 2.4. Assumptions and Limitations
  • 2.5. Sources of Research
    • 2.5.1. Secondary Research
    • 2.5.2. Primary Research
  • 2.6. Approach for the Market Study
    • 2.6.1. The Bottom-Up Approach
    • 2.6.2. The Top-Down Approach
  • 2.7. Methodology Followed for Calculation of Market Size & Market Shares
  • 2.8. Forecasting Methodology
    • 2.8.1. Data Triangulation & Validation

3. Executive Summary

4. Voice of Customer

5. Global Retail Edge Computing Market Overview

6. Global Retail Edge Computing Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Component (Hardware, Software, Services)
    • 6.2.2. By Application (Smart Cities, Industrial Internet of Things, Remote Monitoring, Content Delivery, Augmented Reality, Virtual Reality, Others)
    • 6.2.3. By Organization Size (Small & Medium Enterprises, Large Enterprises)
    • 6.2.4. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
  • 6.3. By Company (2024)
  • 6.4. Market Map

7. North America Retail Edge Computing Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Component
    • 7.2.2. By Application
    • 7.2.3. By Organization Size
    • 7.2.4. By Country
  • 7.3. North America: Country Analysis
    • 7.3.1. United States Retail Edge Computing Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Component
        • 7.3.1.2.2. By Application
        • 7.3.1.2.3. By Organization Size
    • 7.3.2. Canada Retail Edge Computing Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Component
        • 7.3.2.2.2. By Application
        • 7.3.2.2.3. By Organization Size
    • 7.3.3. Mexico Retail Edge Computing Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Component
        • 7.3.3.2.2. By Application
        • 7.3.3.2.3. By Organization Size

8. Europe Retail Edge Computing Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Component
    • 8.2.2. By Application
    • 8.2.3. By Organization Size
    • 8.2.4. By Country
  • 8.3. Europe: Country Analysis
    • 8.3.1. Germany Retail Edge Computing Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Component
        • 8.3.1.2.2. By Application
        • 8.3.1.2.3. By Organization Size
    • 8.3.2. France Retail Edge Computing Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Component
        • 8.3.2.2.2. By Application
        • 8.3.2.2.3. By Organization Size
    • 8.3.3. United Kingdom Retail Edge Computing Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Component
        • 8.3.3.2.2. By Application
        • 8.3.3.2.3. By Organization Size
    • 8.3.4. Italy Retail Edge Computing Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Component
        • 8.3.4.2.2. By Application
        • 8.3.4.2.3. By Organization Size
    • 8.3.5. Spain Retail Edge Computing Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Component
        • 8.3.5.2.2. By Application
        • 8.3.5.2.3. By Organization Size
    • 8.3.6. Belgium Retail Edge Computing Market Outlook
      • 8.3.6.1. Market Size & Forecast
        • 8.3.6.1.1. By Value
      • 8.3.6.2. Market Share & Forecast
        • 8.3.6.2.1. By Component
        • 8.3.6.2.2. By Application
        • 8.3.6.2.3. By Organization Size

9. Asia Pacific Retail Edge Computing Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Component
    • 9.2.2. By Application
    • 9.2.3. By Organization Size
    • 9.2.4. By Country
  • 9.3. Asia Pacific: Country Analysis
    • 9.3.1. China Retail Edge Computing Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Component
        • 9.3.1.2.2. By Application
        • 9.3.1.2.3. By Organization Size
    • 9.3.2. India Retail Edge Computing Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Component
        • 9.3.2.2.2. By Application
        • 9.3.2.2.3. By Organization Size
    • 9.3.3. Japan Retail Edge Computing Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Component
        • 9.3.3.2.2. By Application
        • 9.3.3.2.3. By Organization Size
    • 9.3.4. South Korea Retail Edge Computing Market Outlook
      • 9.3.4.1. Market Size & Forecast
        • 9.3.4.1.1. By Value
      • 9.3.4.2. Market Share & Forecast
        • 9.3.4.2.1. By Component
        • 9.3.4.2.2. By Application
        • 9.3.4.2.3. By Organization Size
    • 9.3.5. Australia Retail Edge Computing Market Outlook
      • 9.3.5.1. Market Size & Forecast
        • 9.3.5.1.1. By Value
      • 9.3.5.2. Market Share & Forecast
        • 9.3.5.2.1. By Component
        • 9.3.5.2.2. By Application
        • 9.3.5.2.3. By Organization Size
    • 9.3.6. Indonesia Retail Edge Computing Market Outlook
      • 9.3.6.1. Market Size & Forecast
        • 9.3.6.1.1. By Value
      • 9.3.6.2. Market Share & Forecast
        • 9.3.6.2.1. By Component
        • 9.3.6.2.2. By Application
        • 9.3.6.2.3. By Organization Size
    • 9.3.7. Vietnam Retail Edge Computing Market Outlook
      • 9.3.7.1. Market Size & Forecast
        • 9.3.7.1.1. By Value
      • 9.3.7.2. Market Share & Forecast
        • 9.3.7.2.1. By Component
        • 9.3.7.2.2. By Application
        • 9.3.7.2.3. By Organization Size

10. South America Retail Edge Computing Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Component
    • 10.2.2. By Application
    • 10.2.3. By Organization Size
    • 10.2.4. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Retail Edge Computing Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Component
        • 10.3.1.2.2. By Application
        • 10.3.1.2.3. By Organization Size
    • 10.3.2. Colombia Retail Edge Computing Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Component
        • 10.3.2.2.2. By Application
        • 10.3.2.2.3. By Organization Size
    • 10.3.3. Argentina Retail Edge Computing Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Component
        • 10.3.3.2.2. By Application
        • 10.3.3.2.3. By Organization Size
    • 10.3.4. Chile Retail Edge Computing Market Outlook
      • 10.3.4.1. Market Size & Forecast
        • 10.3.4.1.1. By Value
      • 10.3.4.2. Market Share & Forecast
        • 10.3.4.2.1. By Component
        • 10.3.4.2.2. By Application
        • 10.3.4.2.3. By Organization Size

11. Middle East & Africa Retail Edge Computing Market Outlook

  • 11.1. Market Size & Forecast
    • 11.1.1. By Value
  • 11.2. Market Share & Forecast
    • 11.2.1. By Component
    • 11.2.2. By Application
    • 11.2.3. By Organization Size
    • 11.2.4. By Country
  • 11.3. Middle East & Africa: Country Analysis
    • 11.3.1. Saudi Arabia Retail Edge Computing Market Outlook
      • 11.3.1.1. Market Size & Forecast
        • 11.3.1.1.1. By Value
      • 11.3.1.2. Market Share & Forecast
        • 11.3.1.2.1. By Component
        • 11.3.1.2.2. By Application
        • 11.3.1.2.3. By Organization Size
    • 11.3.2. UAE Retail Edge Computing Market Outlook
      • 11.3.2.1. Market Size & Forecast
        • 11.3.2.1.1. By Value
      • 11.3.2.2. Market Share & Forecast
        • 11.3.2.2.1. By Component
        • 11.3.2.2.2. By Application
        • 11.3.2.2.3. By Organization Size
    • 11.3.3. South Africa Retail Edge Computing Market Outlook
      • 11.3.3.1. Market Size & Forecast
        • 11.3.3.1.1. By Value
      • 11.3.3.2. Market Share & Forecast
        • 11.3.3.2.1. By Component
        • 11.3.3.2.2. By Application
        • 11.3.3.2.3. By Organization Size
    • 11.3.4. Turkey Retail Edge Computing Market Outlook
      • 11.3.4.1. Market Size & Forecast
        • 11.3.4.1.1. By Value
      • 11.3.4.2. Market Share & Forecast
        • 11.3.4.2.1. By Component
        • 11.3.4.2.2. By Application
        • 11.3.4.2.3. By Organization Size
    • 11.3.5. Israel Retail Edge Computing Market Outlook
      • 11.3.5.1. Market Size & Forecast
        • 11.3.5.1.1. By Value
      • 11.3.5.2. Market Share & Forecast
        • 11.3.5.2.1. By Component
        • 11.3.5.2.2. By Application
        • 11.3.5.2.3. By Organization Size

12. Market Dynamics

  • 12.1. Drivers
  • 12.2. Challenges

13. Market Trends and Developments

14. Company Profiles

  • 14.1. Amazon.com, Inc.
    • 14.1.1. Business Overview
    • 14.1.2. Key Revenue and Financials
    • 14.1.3. Recent Developments
    • 14.1.4. Key Personnel/Key Contact Person
    • 14.1.5. Key Product/Services Offered
  • 14.2. Microsoft Corporation
    • 14.2.1. Business Overview
    • 14.2.2. Key Revenue and Financials
    • 14.2.3. Recent Developments
    • 14.2.4. Key Personnel/Key Contact Person
    • 14.2.5. Key Product/Services Offered
  • 14.3. IBM Corporation
    • 14.3.1. Business Overview
    • 14.3.2. Key Revenue and Financials
    • 14.3.3. Recent Developments
    • 14.3.4. Key Personnel/Key Contact Person
    • 14.3.5. Key Product/Services Offered
  • 14.4. Intel Corporation
    • 14.4.1. Business Overview
    • 14.4.2. Key Revenue and Financials
    • 14.4.3. Recent Developments
    • 14.4.4. Key Personnel/Key Contact Person
    • 14.4.5. Key Product/Services Offered
  • 14.5. Cisco Systems, Inc.
    • 14.5.1. Business Overview
    • 14.5.2. Key Revenue and Financials
    • 14.5.3. Recent Developments
    • 14.5.4. Key Personnel/Key Contact Person
    • 14.5.5. Key Product/Services Offered
  • 14.6. Hewlett Packard Enterprise Company
    • 14.6.1. Business Overview
    • 14.6.2. Key Revenue and Financials
    • 14.6.3. Recent Developments
    • 14.6.4. Key Personnel/Key Contact Person
    • 14.6.5. Key Product/Services Offered
  • 14.7. NVIDIA Corporation
    • 14.7.1. Business Overview
    • 14.7.2. Key Revenue and Financials
    • 14.7.3. Recent Developments
    • 14.7.4. Key Personnel/Key Contact Person
    • 14.7.5. Key Product/Services Offered
  • 14.8. Google LLC
    • 14.8.1. Business Overview
    • 14.8.2. Key Revenue and Financials
    • 14.8.3. Recent Developments
    • 14.8.4. Key Personnel/Key Contact Person
    • 14.8.5. Key Product/Services Offered
  • 14.9. Oracle Corporation
    • 14.9.1. Business Overview
    • 14.9.2. Key Revenue and Financials
    • 14.9.3. Recent Developments
    • 14.9.4. Key Personnel/Key Contact Person
    • 14.9.5. Key Product/Services Offered
  • 14.10. Qualcomm Incorporated
    • 14.10.1. Business Overview
    • 14.10.2. Key Revenue and Financials
    • 14.10.3. Recent Developments
    • 14.10.4. Key Personnel/Key Contact Person
    • 14.10.5. Key Product/Services Offered

15. Strategic Recommendations

16. About Us & Disclaimer