The adoption of automated people mover in Japan is set to exhibit a CAGR of 5.8% through 2034. The demand for automated people mover in Japan is poised to witness significant opportunities, reaching US$ 195.52 million in 2024. Automated people mover is becoming an integral component of transportation systems, providing seamless connectivity between various modes of transit. This trend addresses the growing need for efficient and convenient transportation solutions. By 2034, the sales of automated people mover in Japan is likely to secure a valuation of US$ 346.10 million.
| Attributes | Details |
|---|---|
| Expected Value in 2024 | US$ 195.52 million |
| Projected Value by 2034 | US$ 346.10 million |
| CAGR Estimation from 2024 to 2034 | 5.8% |
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Tokyo, situated in the Kanto region, is among the highly populated and densely inhabited urban areas globally. As urbanization continues and population density increases, there is a greater need for efficient and convenient transportation solutions, potentially driving the demand for automated people mover. Several important airports, including Tokyo Haneda International Airport and Narita International Airport, serve the Kanto region. Automated people mover is commonly used in airports to transport passengers between terminals and facilities. Continued airport expansion and modernization projects could contribute to the growth of automated people mover industry.
Tokyo and other cities in the Kanto region are actively involved in smart city initiatives, focusing on incorporating advanced technologies to enhance urban living. Automated people mover is likely to play a role in these initiatives by providing efficient and technology-driven transportation solutions. The Kanto region includes key business districts and commercial areas. Automated people mover can provide convenient connectivity within these districts, linking office complexes, shopping centers, and public transit hubs.
Chubu is a crucial industrial and economic hub in Japan, housing various manufacturing and technology companies. As industrial activity grows, there may be an increased demand for efficient transportation solutions within industrial complexes and business districts.
Ongoing and planned transportation infrastructure projects in the region, including airport expansions, urban development, and connectivity improvements, may drive the demand for automated people mover. The region's key airport, Chubu Centrair International Airport, could be a key focal point for APM utilization.
As urbanization and population growth occur, the need for efficient and sustainable transportation solutions within urban centers and suburban areas may increase, contributing to the demand for APM systems.
In 2024, the duo rail segment is likely to account for an industry share of 81%. Duo rail takes up less area horizontally and vertically than traditional rail systems. Duo rail vehicles are broader than the beam and are frequently elevated, requiring just a small footprint for support pillars. These factors are expected to fuel sales of duo rail systems in the forthcoming years.
| Attribute | Details |
|---|---|
| System | Duo Rail |
| Value Share in 2024 | 81% |
In 2024, the airport segment is projected to hold an industry share of 61.5%. People mover systems are used in many international airports worldwide to convey passengers between terminals or inside a terminal. Airports often have multiple terminals, each serving different airlines or flight operations. APMs provide a quick and efficient means of connecting passengers between terminals, reducing the time and effort required for transit.
| Attribute | Details |
|---|---|
| Application | Airports |
| Value Share in 2024 | 61.5% |
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Acquisitions and mergers are the default expansion strategies for players operating in the automated people mover industry in Japan. Key manufacturers of automated people mover in Japan focus on facility expansions, product innovations, and promotional activities to increase sales and gain a competitive edge. Key players in the automated people mover ecosystem are also investing to enhance their manufacturing capabilities and geographical footprint, aiming to increase their industry share.
| Attribute | Details |
|---|---|
| Estimated Industry Size in 2024 | US$ 195.52 million |
| Projected Industry Size by 2034 | US$ 346.10 million |
| Anticipated CAGR between 2024 to 2034 | 5.8% CAGR |
| Historical Analysis of Demand for Automated People Mover in Japan | 2019 to 2023 |
| Demand Forecast for Automated People Mover in Japan in Japan | 2024 to 2034 |
| Report Coverage | Industry Size, Industry Trends, Analysis of key factors influencing Automated People Mover in Japan, Insights on Global Players and their Industry Strategy in Japan, Ecosystem Analysis of Local Providers in Japan |
| Key Cities Analyzed while Studying Opportunities in Automated People Mover in Japan |
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| Key Companies Profiled |
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The estimated valuation of the automated people mover in Japan is US$ 195.52 million in 2024.
The anticipated CAGR for the automated people mover ecosystem in Japan through 2034 is 5.8%.
Demand for automated people mover in Japan is likely to reach US$ 346.10 million by 2034.
The airport segment is likely to account for high industry share.
1. Executive Summary 1.1. Market Outlook 1.2. Demand-side Trends 1.3. Supply-side Trends 1.4. Technology Roadmap Analysis 1.5. Analysis and Recommendations 2. Market Overview 2.1. Market Coverage / Taxonomy 2.2. Market Definition / Scope / Limitations 3. Market Background 3.1. Market Dynamics 3.1.1. Drivers 3.1.2. Restraints 3.1.3. Opportunity 3.1.4. Trends 3.2. Scenario Forecast 3.2.1. Demand in Optimistic Scenario 3.2.2. Demand in Likely Scenario 3.2.3. Demand in Conservative Scenario 3.3. Opportunity Map Analysis 3.4. Product Life Cycle Analysis 3.5. Supply Chain Analysis 3.5.1. Supply Side Participants and their Roles 3.5.1.1. Producers 3.5.1.2. Mid-Level Participants (Traders/ Agents/ Brokers) 3.5.1.3. Wholesalers and Distributors 3.5.2. Value Added and Value Created at Node in the Supply Chain 3.5.3. List of Raw Material Suppliers 3.5.4. List of Existing and Potential Buyer’s 3.6. Investment Feasibility Matrix 3.7. Value Chain Analysis 3.7.1. Profit Margin Analysis 3.7.2. Wholesalers and Distributors 3.7.3. Retailers 3.8. PESTLE and Porter’s Analysis 3.9. Regulatory Landscape 3.9.1. By Key Regions 3.10. Regional Parent Market Outlook 3.11. Production and Consumption Statistics 3.12. Import and Export Statistics 4. Industry Analysis and Outlook 2018 to 2022 and Forecast, 2023 to 2033 4.1. Historical Market Size Value (US$ Million) & Volume (Units) Analysis, 2018 to 2022 4.2. Current and Future Market Size Value (US$ Million) & Volume (Units) Projections, 2023 to 2033 4.2.1. Y-o-Y Growth Trend Analysis 4.2.2. Absolute $ Opportunity Analysis 5. Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033, By System Type 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Million) & Volume (Units) Analysis By System Type, 2018 to 2022 5.3. Current and Future Market Size Value (US$ Million) & Volume (Units) Analysis and Forecast By System Type, 2023 to 2033 5.3.1. Monorail 5.3.2. Duo Rail 5.3.3. Automated Guide Way Transit or Maglev 5.4. Y-o-Y Growth Trend Analysis By System Type, 2018 to 2022 5.5. Absolute $ Opportunity Analysis By System Type, 2023 to 2033 6. Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033, By Application 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Million) & Volume (Units) Analysis By Application, 2018 to 2022 6.3. Current and Future Market Size Value (US$ Million) & Volume (Units) Analysis and Forecast By Application, 2023 to 2033 6.3.1. Airport 6.3.2. Urban Transit 6.3.3. Amusements Parks 6.3.4. Shopping or Commercial Centres 6.3.5. Others 6.4. Y-o-Y Growth Trend Analysis By Application, 2018 to 2022 6.5. Absolute $ Opportunity Analysis By Application, 2023 to 2033 7. Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033, By Region 7.1. Introduction 7.2. Historical Market Size Value (US$ Million) & Volume (Units) Analysis By Region, 2018 to 2022 7.3. Current Market Size Value (US$ Million) & Volume (Units) Analysis and Forecast By Region, 2023 to 2033 7.3.1. Kanto 7.3.2. Chubu 7.3.3. Kinki 7.3.4. Kyushu & Okinawa 7.3.5. Tohoku 7.3.6. Rest of Japan 7.4. Market Attractiveness Analysis By Region 8. Kanto Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033 8.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2018 to 2022 8.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2023 to 2033 8.2.1. By System Type 8.2.2. By Application 8.3. Market Attractiveness Analysis 8.3.1. By System Type 8.3.2. By Application 8.4. Key Takeaways 9. Chubu Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033 9.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2018 to 2022 9.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2023 to 2033 9.2.1. By System Type 9.2.2. By Application 9.3. Market Attractiveness Analysis 9.3.1. By System Type 9.3.2. By Application 9.4. Key Takeaways 10. Kinki Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033 10.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2018 to 2022 10.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2023 to 2033 10.2.1. By System Type 10.2.2. By Application 10.3. Market Attractiveness Analysis 10.3.1. By System Type 10.3.2. By Application 10.4. Key Takeaways 11. Kyushu & Okinawa Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033 11.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2018 to 2022 11.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2023 to 2033 11.2.1. By System Type 11.2.2. By Application 11.3. Market Attractiveness Analysis 11.3.1. By System Type 11.3.2. By Application 11.4. Key Takeaways 12. Tohoku Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033 12.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2018 to 2022 12.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2023 to 2033 12.2.1. By System Type 12.2.2. By Application 12.3. Market Attractiveness Analysis 12.3.1. By System Type 12.3.2. By Application 12.4. Key Takeaways 13. Rest of Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033 13.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2018 to 2022 13.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2023 to 2033 13.2.1. By System Type 13.2.2. By Application 13.3. Market Attractiveness Analysis 13.3.1. By System Type 13.3.2. By Application 13.4. Key Takeaways 14. Market Structure Analysis 14.1. Competition Dashboard 14.2. Competition Benchmarking 14.3. Market Share Analysis of Top Players 14.3.1. By Regional 14.3.2. By System Type 14.3.3. By Application 15. Competition Analysis 15.1. Competition Deep Dive 15.1.1. Siemens 15.1.1.1. Overview 15.1.1.2. Product Portfolio 15.1.1.3. Profitability by Market Segments 15.1.1.4. Sales Footprint 15.1.1.5. Strategy Overview 15.1.1.5.1. Marketing Strategy 15.1.1.5.2. Product Strategy 15.1.1.5.3. Channel Strategy 15.1.2. MITSUBISHI HEAVY INDUSTRIES, LTD. 15.1.2.1. Overview 15.1.2.2. Product Portfolio 15.1.2.3. Profitability by Market Segments 15.1.2.4. Sales Footprint 15.1.2.5. Strategy Overview 15.1.2.5.1. Marketing Strategy 15.1.2.5.2. Product Strategy 15.1.2.5.3. Channel Strategy 15.1.3. Doppelmayr Seilbahnen GmbH 15.1.3.1. Overview 15.1.3.2. Product Portfolio 15.1.3.3. Profitability by Market Segments 15.1.3.4. Sales Footprint 15.1.3.5. Strategy Overview 15.1.3.5.1. Marketing Strategy 15.1.3.5.2. Product Strategy 15.1.3.5.3. Channel Strategy 15.1.4. PT Len Industri (Persero) 15.1.4.1. Overview 15.1.4.2. Product Portfolio 15.1.4.3. Profitability by Market Segments 15.1.4.4. Sales Footprint 15.1.4.5. Strategy Overview 15.1.4.5.1. Marketing Strategy 15.1.4.5.2. Product Strategy 15.1.4.5.3. Channel Strategy 15.1.5. LEITNER AG 15.1.5.1. Overview 15.1.5.2. Product Portfolio 15.1.5.3. Profitability by Market Segments 15.1.5.4. Sales Footprint 15.1.5.5. Strategy Overview 15.1.5.5.1. Marketing Strategy 15.1.5.5.2. Product Strategy 15.1.5.5.3. Channel Strategy 15.1.6. Coester Group 15.1.6.1. Overview 15.1.6.2. Product Portfolio 15.1.6.3. Profitability by Market Segments 15.1.6.4. Sales Footprint 15.1.6.5. Strategy Overview 15.1.6.5.1. Marketing Strategy 15.1.6.5.2. Product Strategy 15.1.6.5.3. Channel Strategy 15.1.7. HYUNDAI ROTEM COMPANY 15.1.7.1. Overview 15.1.7.2. Product Portfolio 15.1.7.3. Profitability by Market Segments 15.1.7.4. Sales Footprint 15.1.7.5. Strategy Overview 15.1.7.5.1. Marketing Strategy 15.1.7.5.2. Product Strategy 15.1.7.5.3. Channel Strategy 15.1.8. IHI Corporation 15.1.8.1. Overview 15.1.8.2. Product Portfolio 15.1.8.3. Profitability by Market Segments 15.1.8.4. Sales Footprint 15.1.8.5. Strategy Overview 15.1.8.5.1. Marketing Strategy 15.1.8.5.2. Product Strategy 15.1.8.5.3. Channel Strategy 15.1.9. Alstom 15.1.9.1. Overview 15.1.9.2. Product Portfolio 15.1.9.3. Profitability by Market Segments 15.1.9.4. Sales Footprint 15.1.9.5. Strategy Overview 15.1.9.5.1. Marketing Strategy 15.1.9.5.2. Product Strategy 15.1.9.5.3. Channel Strategy 15.1.10. Bombardier 15.1.10.1. Overview 15.1.10.2. Product Portfolio 15.1.10.3. Profitability by Market Segments 15.1.10.4. Sales Footprint 15.1.10.5. Strategy Overview 15.1.10.5.1. Marketing Strategy 15.1.10.5.2. Product Strategy 15.1.10.5.3. Channel Strategy 16. Assumptions & Acronyms Used 17. Research Methodology
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Automated People Mover Industry Analysis in Japan
