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Global Tech Savvy Hotel Chains Market to reach USD XX million by 2028.

Global Tech Savvy Hotel Chains Market Size study, By Price Level ( Luxury, Upscale, Midscale, Economy), By Room Capacity (Small, Medium, Large, Mega), By Application (Urban, Airport, Resorts, Other Applications), By Technology (Contactless Check-in, Temperature Control, Digitally Interactive Displays, Robotic Luggage Concierge), and Regional Forecasts 2022-2028

Product Code: OIRTT-21987872
Publish Date: 5-07-2022
Page: 200

Global Tech Savvy Hotel Chains Market is valued approximately USD XX million in 2021 and is anticipated to grow with a healthy growth rate of more than XX % over the forecast period 2022-2028. The Tech Savvy Hotel Chains can be defined as hotel properties that eliminates the traditional touchstones of the hotel experience. Tech savvy hotels make use of different technologies such as internet-connected devices, blockchain technology and robotics technology among others. Tech savvy hotels offers several advantages and facilities such as automated luggage storage for guests, app & RFID wristbands-based check-in, locking & unlocking of doors among others. The growing digitization in hospitality sector and increasing Internet of Things (IoT) spending in hospitality industry as well as strategic initiatives from leading market players are factors that are accelerating the global market demand. For instance, according to Statista – in 2020, the worldwide smart hospitality sector was valued at USD 6 billion, and this amount is projected to grow to USD 24.98 billion by 2027, witnessing a compound annual growth rate (CAGR) of 22.6 percent. Furthermore, leading market players are working towards strategic initiatives such as market expansion, and new technological advancements to leverage the increasing inclination towards Tech Savvy Hotels. For instance, in October 2019, Amsterdam, Netherlands based tech savvy hotel chain CityHub launched its new chain in Copenhagen, Denmark. This new facility would be CityHub’s first property outside The Netherlands and would be the biggest CityHub property so far. Moreover, in May 2022, New York, USA based NoMo SoHo Hotel launched a blockchain technology based curated NFT named NFT Stays. These specially curated NFTs, packaged with three- to six-night stays at NoMo SoHo. Also, growing tourism sector in emerging economies and rapid urbanization & increasing per capita travel spending are anticipated to act as a catalyzing factor for the market demand during the forecast period. However, a high initial capital requirement and periodic maintenance & upgradation requirement impede the growth of the market over the forecast period of 2022-2028.

The key regions considered for the global Tech Savvy Hotel Chains Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America is the leading region across the world in terms of market share owing to the growing digitization across different industries and presence of leading market players. Whereas, Asia Pacific is anticipated to exhibit a significant growth rate over the forecast period 2022-2028. Factors such as the thriving growth of tourism sector and increasing penetration of 5G, IoT technologies in the region, would create lucrative growth prospects for the global Tech Savvy Hotel Chains Market across the Asia Pacific region.

Major market players included in this report are:
W Singapore
The Hotel Silken Puerta América
The Yotel New York City
Eccleston Square Pimlico
Pengheng Space Capsules Hotel
Blow Up Hall 5050
City Hub
Kameha Grand
Hotel Zetta
Henn Na Hotel

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Price Level
Luxury
Upscale
Midscale
Economy
By Room Capacity
Small
Medium
Large
Mega
By Application
Urban
Airport
Resorts
Other Applications
By Technology
Contactless Check-in
Temperature Control
Digitally Interactive Displays
Robotic Luggage Concierge
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Tech Savvy Hotel Chains Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Million)
1.2.1. Global Tech Savvy Hotel Chains Market, by Region, 2020-2028 (USD Million)
1.2.2. Global Tech Savvy Hotel Chains Market, by Price Level, 2020-2028 (USD Million)
1.2.3. Global Tech Savvy Hotel Chains Market, by Room Capacity, 2020-2028 (USD Million)
1.2.4. Global Tech Savvy Hotel Chains Market, by Application, 2020-2028 (USD Million)
1.2.5. Global Tech Savvy Hotel Chains Market, by Technology, 2020-2028 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Tech Savvy Hotel Chains Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Tech Savvy Hotel Chains Market Dynamics
3.1. Tech Savvy Hotel Chains Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Growing digitization in hospitality sector.
3.1.1.2. Increasing Internet of Things (IoT) spending in hospitality industry.
3.1.1.3. Strategic initiatives from leading market players.
3.1.2. Market Challenges
3.1.2.1. High initial capital requirement.
3.1.2.2. Periodic maintenance & upgradation requirement.
3.1.3. Market Opportunities
3.1.3.1. Growing tourism sector in emerging economies.
3.1.3.2. Rapid urbanization & increasing per capita travel spending.
Chapter 4. Global Tech Savvy Hotel Chains Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Tech Savvy Hotel Chains Market, by Price Level
6.1. Market Snapshot
6.2. Global Tech Savvy Hotel Chains Market by Price Level, Performance – Potential Analysis
6.3. Global Tech Savvy Hotel Chains Market Estimates & Forecasts by Price Level 2018-2028 (USD Million)
6.4. Tech Savvy Hotel Chains Market, Sub Segment Analysis
6.4.1. Luxury
6.4.2. Upscale
6.4.3. Midscale
6.4.4. Economy
Chapter 7. Global Tech Savvy Hotel Chains Market, by Room Capacity
7.1. Market Snapshot
7.2. Global Tech Savvy Hotel Chains Market by Room Capacity, Performance – Potential Analysis
7.3. Global Tech Savvy Hotel Chains Market Estimates & Forecasts by Room Capacity 2018-2028 (USD Million)
7.4. Tech Savvy Hotel Chains Market, Sub Segment Analysis
7.4.1. Small
7.4.2. Medium
7.4.3. Large
7.4.4. Mega
Chapter 8. Global Tech Savvy Hotel Chains Market, by Application
8.1. Market Snapshot
8.2. Global Tech Savvy Hotel Chains Market by Application, Performance – Potential Analysis
8.3. Global Tech Savvy Hotel Chains Market Estimates & Forecasts by Application 2018-2028 (USD Million)
8.4. Tech Savvy Hotel Chains Market, Sub Segment Analysis
8.4.1. Urban
8.4.2. Airport
8.4.3. Resorts
8.4.4. Other Applications
Chapter 9. Global Tech Savvy Hotel Chains Market, by Technology
9.1. Market Snapshot
9.2. Global Tech Savvy Hotel Chains Market by Technology, Performance – Potential Analysis
9.3. Global Tech Savvy Hotel Chains Market Estimates & Forecasts by Technology 2018-2028 (USD Million)
9.4. Tech Savvy Hotel Chains Market, Sub Segment Analysis
9.4.1. Contactless Check-in
9.4.2. Temperature Control
9.4.3. Digitally Interactive Displays
9.4.4. Robotic Luggage Concierge
Chapter 10. Global Tech Savvy Hotel Chains Market, Regional Analysis
10.1. Tech Savvy Hotel Chains Market, Regional Market Snapshot
10.2. North America Tech Savvy Hotel Chains Market
10.2.1. U.S. Tech Savvy Hotel Chains Market
10.2.1.1. Price Level estimates & forecasts, 2018-2028
10.2.1.2. Room Capacity estimates & forecasts, 2018-2028
10.2.1.3. Application estimates & forecasts, 2018-2028
10.2.1.4. Technology estimates & forecasts, 2018-2028
10.2.2. Canada Tech Savvy Hotel Chains Market
10.3. Europe Tech Savvy Hotel Chains Market Snapshot
10.3.1. U.K. Tech Savvy Hotel Chains Market
10.3.2. Germany Tech Savvy Hotel Chains Market
10.3.3. France Tech Savvy Hotel Chains Market
10.3.4. Spain Tech Savvy Hotel Chains Market
10.3.5. Italy Tech Savvy Hotel Chains Market
10.3.6. Rest of Europe Tech Savvy Hotel Chains Market
10.4. Asia-Pacific Tech Savvy Hotel Chains Market Snapshot
10.4.1. China Tech Savvy Hotel Chains Market
10.4.2. India Tech Savvy Hotel Chains Market
10.4.3. Japan Tech Savvy Hotel Chains Market
10.4.4. Australia Tech Savvy Hotel Chains Market
10.4.5. South Korea Tech Savvy Hotel Chains Market
10.4.6. Rest of Asia Pacific Tech Savvy Hotel Chains Market
10.5. Latin America Tech Savvy Hotel Chains Market Snapshot
10.5.1. Brazil Tech Savvy Hotel Chains Market
10.5.2. Mexico Tech Savvy Hotel Chains Market
10.6. Rest of The World Tech Savvy Hotel Chains Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. W Singapore
11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Product Summary
11.2.1.5. Recent Developments
11.2.2. The Hotel Silken Puerta América
11.2.3. The Yotel New York City
11.2.4. Eccleston Square Pimlico
11.2.5. Pengheng Space Capsules Hotel
11.2.6. Blow Up Hall 5050
11.2.7. City Hub
11.2.8. Kameha Grand
11.2.9. Hotel Zetta
11.2.10. Henn Na Hotel
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

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Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
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To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
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To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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