Report Content
Chapter 1 Methodology & Scope
1.1 Research design
1.1.1 Research approach
1.1.2 Data collection methods
1.2 Base estimates and calculations
1.2.1 Base year calculation
1.2.2 Key trends for market estimates
1.3 Forecast model
1.4 Primary research & validation
1.4.1 Primary sources
1.4.2 Data mining sources
1.5 Market definitions
Chapter 2 Executive Summary
2.1 Industry 3600 synopsis, 2021-2032
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.2 Supplier landscape
3.2.1 Insurance providers
3.2.2 Distribution channels
3.2.3 End users
3.3 Profit margin analysis
3.4 Technology & innovation landscape
3.5 Patent analysis
3.6 Key news & initiatives
3.7 Regulatory landscape
3.8 Impact forces
3.8.1 Growth drivers
3.8.1.1 Supply chain and route planning optimization
3.8.1.2 Increased demand for warehouse management
3.8.1.3 Accuracy in demand forecasting
3.8.1.4 Achieving cost efficiency
3.9 Industry pitfalls & challenges
3.9.1.1 Data quality and availability
3.9.1.2 Complexity in integration
3.10 Growth potential analysis
3.11 Porter’s analysis
3.12 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 & Forecast, By Type, 2021-2032 ($Bn)
5.1 Key trends
5.2 Variational Autoencoder (VAE)
5.3 Generative Adversarial Networks (GANs)
5.4 Recurrent Neural Networks (RNNs)
5.5 Long Short-Term Memory (LSTM) networks
5.6 Others
Chapter 6 Market Estimate & Forecast, By Component, 2021-2032 ($Bn)
6.1 Key trends
6.2 Software
6.3 Services
Chapter 7 Market Estimates & Forecast, By Deployment Mode, 2021-2032 ($Bn)
7.1 Key trends
7.2 Cloud
7.3 On-premises
Chapter 8 Market Estimates & Forecast, By Application, 2021-2032 ($Bn)
8.1 Key trends
8.2 Route optimization
8.2.1 Variational Autoencoder (VAE)
8.2.2 Generative Adversarial Networks (GANs)
8.2.3 Recurrent Neural Networks (RNNs)
8.2.4 Long Short-Term Memory (LSTM) networks
8.2.5 Others
8.3 Demand forecasting
8.3.1 Variational Autoencoder (VAE)
8.3.2 Generative Adversarial Networks (GANs)
8.3.3 Recurrent Neural Networks (RNNs)
8.3.4 Long Short-Term Memory (LSTM) networks
8.3.5 Others
8.4 Warehouse and inventory management
8.4.1 Variational Autoencoder (VAE)
8.4.2 Generative Adversarial Networks (GANs)
8.4.3 Recurrent Neural Networks (RNNs)
8.4.4 Long Short-Term Memory (LSTM) networks
8.4.5 Others
8.5 Supply chain automation
8.5.1 Variational Autoencoder (VAE)
8.5.2 Generative Adversarial Networks (GANs)
8.5.3 Recurrent Neural Networks (RNNs)
8.5.4 Long Short-Term Memory (LSTM) networks
8.5.5 Others
8.6 Predictive maintenance
8.6.1 Variational Autoencoder (VAE)
8.6.2 Generative Adversarial Networks (GANs)
8.6.3 Recurrent Neural Networks (RNNs)
8.6.4 Long Short-Term Memory (LSTM) networks
8.6.5 Others
8.7 Risk management
8.7.1 Variational Autoencoder (VAE)
8.7.2 Generative Adversarial Networks (GANs)
8.7.3 Recurrent Neural Networks (RNNs)
8.7.4 Long Short-Term Memory (LSTM) networks
8.7.5 Others
8.8 Customized logistics solutions
8.8.1 Variational Autoencoder (VAE)
8.8.2 Generative Adversarial Networks (GANs)
8.8.3 Recurrent Neural Networks (RNNs)
8.8.4 Long Short-Term Memory (LSTM) networks
8.8.5 Others
8.9 Others
8.9.1 Variational Autoencoder (VAE)
8.9.2 Generative Adversarial Networks (GANs)
8.9.3 Recurrent Neural Networks (RNNs)
8.9.4 Long Short-Term Memory (LSTM) networks
8.9.5 Others
Chapter 9 Market Estimates & Forecast, By End User, 2021-2032 ($Bn)
9.1 Key trends
9.2 Road Transportation
9.3 Railway Transport
9.4 Aviation
9.5 Shipping, and Ports
Chapter 10 Market Estimates & Forecast, By Region, 2021-2032 ($Bn)
10.1 Key trends
10.2 North America
10.2.1 U.S.
10.2.2 Canada
10.3 Europe
10.3.1 UK
10.3.2 Germany
10.3.3 France
10.3.4 Italy
10.3.5 Spain
10.3.6 Russia
10.3.7 Nordics
10.3.8 Rest of Europe
10.4 Asia Pacific
10.4.1 China
10.4.2 India
10.4.3 Japan
10.4.4 South Korea
10.4.5 ANZ
10.4.6 Southeast Asia
10.4.7 Rest of Asia Pacific
10.5 Latin America
10.5.1 Brazil
10.5.2 Mexico
10.5.3 Argentina
10.5.4 Rest of Latin America
10.6 MEA
10.6.1 South Africa
10.6.2 Saudi Arabia
10.6.3 UAE
10.6.4 Rest of MEA
Chapter 11 Company Profiles
11.1 Blue Yonder
11.2 C.H. Robinson
11.3 DHL
11.4 FedEx Corp
11.5 Google Cloud
11.6 IBM
11.7 LeewayHertz
11.8 Microsoft
11.9 Nexocode
11.10 PackageX
11.11 Salesforce
11.12 SAP SE
11.13 Schneider Electric
11.14 UPS (United Parcel Services)
11.15 XenonStack
11.16 XPO Logistics
