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Global Laundry Appliances Market to reach USD XX billion by the end of 2030.

Global Laundry Appliances Market Size Study & Forecast, by Type (Free Standing, built in) by Product (Washing Machine, Dryers, Electric Smoothing Irons, Others), by Technology (Automatic, Semi-Automatic/Manual, and Others), by Distribution Channel (Multi-brand Stores, Exclusive Stores, Online, and Other Distribution Channels) and Regional Analysis, 2023-2030

Product Code: OIRHG-33975222
Publish Date: 10-09-2023
Page: 200

Global Laundry Appliances Market is valued at approximately USD XX billion in 2022 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2023-2030. Laundry appliances refer to household machines and equipment designed specifically for washing, drying, and maintaining clean clothing and other textiles. These appliances include washing machines, dryers, and combination washer-dryer units that automate the process of cleaning and caring for clothes, linens, and other fabric-based items. The expansion of the laundry appliances market is driven by factors such as the growing middle-class population’s purchasing capacity of washing machines and dryers. The increasing number of women in the workforce also contributes to the demand for appliances such as washing machines, which assist with household chores.

The market for laundry appliances is driven by the increasing adoption of smart homes. The integration of smart technologies in households is fueling the demand for advanced and connected laundry appliances that offer convenience, efficiency, and remote-control capabilities. As per Alarms.org’s data in 2022, the adoption of smart products in households is experiencing significant growth. According to Statista, in 2021, there were approximately 262.57 million users of smart homes were recorded around the world. Also, the figure is constantly rising and is projected to reach 672.57 million users by 2027. Moreover, current trends in the laundry appliances market involve a focus on innovation to enhance efficiency, energy efficiency, and water consumption in line with environmental regulations set by various governments. Additionally, the growing levels of disposable income of the population are driving the demand for laundry appliances. However, high initial costs associated with purchasing advanced and energy-efficient appliances, and the need for proper maintenance and repair services stifle market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Laundry Appliances Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. Europe dominated the market in 2022. The widespread adoption of automatic washing processes as a fundamental aspect of daily household chores among Europeans has generated promising growth opportunities in the region. In addition, rapid urbanization and changing lifestyles, advancements in laundry appliance technologies, and growing awareness of environmental issues and energy conservation are the further attributing to the regional market growth. North America is expected as the fastest growing during the forecast period, the growing preference for smart devices and smart homes among Americans is driving the sales of smart washing machines, as connected devices gain increasing prominence.

Major market players included in this report are:
Whirlpool
Alliance Laundry Systems LLC
Videocon Industries Limited
Robert Bosch GmbH
Toshiba Corporation
Candy Hoover Group S.p.A.
Sharp Corporation
Electrolux AB
GD Midea Holding Co. Ltd.
Samsung Electronics Co., Ltd.

Recent Developments in the Market:
Ø In August 2020, Samsung launched an AI-powered laundry lineup that includes washing machines with top-tier energy efficiency. These innovative machines utilize artificial intelligence (AI) capabilities to customize the laundry process, achieving a powerful wash while saving time, energy, and effort. The lineup also features Samsung’s EcoBubble and QuickDrive technology.
Ø In January 2021, LG Electronics unveiled the LG ThinQ front-load washing machine, which incorporates an Artificial Intelligent Direct Drive (AI DD) motor. This advanced motor not only detects the weight of the load but also senses the fabric’s softness, enabling it to automatically select the optimal motions for different types of fabric. The LG ThinQ washing machine is conveniently controlled using the Smart ThinQ Wi-Fi, allowing users to operate the machine remotely from any location, creating a seamless and integrated experience.
Global Laundry Appliances Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Type, Product, Technology, Distribution Channel, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

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 years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential 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 Type:
Freestanding
Built in

By Product:
Washing Machine
Dryers
Electric Smoothing Irons
Others

By Technology:
Automatic
Semi-Automatic/ Manual
Others

By Distribution Channel:
Multi-brand Stores
Exclusive Stores
Online
Other Distribution Channels

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

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Laundry Appliances Market, by Region, 2020-2030 (USD Billion)
1.2.2. Laundry Appliances Market, by Type, 2020-2030 (USD Billion)
1.2.3. Laundry Appliances Market, by Product, 2020-2030 (USD Billion)
1.2.4. Laundry Appliances Market, by Technology, 2020-2030 (USD Billion)
1.2.5. Laundry Appliances Market, by Distribution Channel, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Laundry Appliances Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Laundry Appliances Market Dynamics
3.1. Laundry Appliances Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increasing number of women in the workforce
3.1.1.2. Growing middle-class population
3.1.2. Market Challenges
3.1.2.1. Need for timely maintenance and repair services
3.1.2.2. High initial costs associated with purchasing energy-efficient appliances
3.1.3. Market Opportunities
3.1.3.1. Technological Advancements in laundry appliances
3.1.3.2. Growing levels of disposable income
Chapter 4. Global Laundry Appliances 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
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Laundry Appliances Market, by Type
5.1. Market Snapshot
5.2. Global Laundry Appliances Market by Type, Performance – Potential Analysis
5.3. Global Laundry Appliances Market Estimates & Forecasts by Type 2020-2030 (USD Billion)
5.4. Laundry Appliances Market, Sub Segment Analysis
5.4.1. Freestanding
5.4.2. Built in
Chapter 6. Global Laundry Appliances Market, by Product
6.1. Market Snapshot
6.2. Global Laundry Appliances Market by Product, Performance – Potential Analysis
6.3. Global Laundry Appliances Market Estimates & Forecasts by Product 2020-2030 (USD Billion)
6.4. Laundry Appliances Market, Sub Segment Analysis
6.4.1. Washing Machine
6.4.2. Dryers
6.4.3. Electric Smoothing Irons
6.4.4. Others
Chapter 7. Global Laundry Appliances Market, by Technology
7.1. Market Snapshot
7.2. Global Laundry Appliances Market by Technology, Performance – Potential Analysis
7.3. Global Laundry Appliances Market Estimates & Forecasts by Technology 2020-2030 (USD Billion)
7.4. Laundry Appliances Market, Sub Segment Analysis
7.4.1. Automatic
7.4.2. Semi-Automatic/ Manual
7.4.3. Others
Chapter 8. Global Laundry Appliances Market, by Distribution Channel
8.1. Market Snapshot
8.2. Global Laundry Appliances Market by Distribution Channel, Performance – Potential Analysis
8.3. Global Laundry Appliances Market Estimates & Forecasts by Distribution Channel 2020-2030 (USD Billion)
8.4. Laundry Appliances Market, Sub Segment Analysis
8.4.1. Multi-brand Stores
8.4.2. Exclusive Stores
8.4.3. Online
8.4.4. Other Distribution Channels
Chapter 9. Global Laundry Appliances Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Laundry Appliances Market, Regional Market Snapshot
9.4. North America Laundry Appliances Market
9.4.1. U.S. Laundry Appliances Market
9.4.1.1. Type breakdown estimates & forecasts, 2020-2030
9.4.1.2. Product breakdown estimates & forecasts, 2020-2030
9.4.1.3. Technology breakdown estimates & forecasts, 2020-2030
9.4.1.4. Distribution Channel breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Laundry Appliances Market
9.5. Europe Laundry Appliances Market Snapshot
9.5.1. U.K. Laundry Appliances Market
9.5.2. Germany Laundry Appliances Market
9.5.3. France Laundry Appliances Market
9.5.4. Spain Laundry Appliances Market
9.5.5. Italy Laundry Appliances Market
9.5.6. Rest of Europe Laundry Appliances Market
9.6. Asia-Pacific Laundry Appliances Market Snapshot
9.6.1. China Laundry Appliances Market
9.6.2. India Laundry Appliances Market
9.6.3. Japan Laundry Appliances Market
9.6.4. Australia Laundry Appliances Market
9.6.5. South Korea Laundry Appliances Market
9.6.6. Rest of Asia Pacific Laundry Appliances Market
9.7. Latin America Laundry Appliances Market Snapshot
9.7.1. Brazil Laundry Appliances Market
9.7.2. Mexico Laundry Appliances Market
9.8. Middle East & Africa Laundry Appliances Market
9.8.1. Saudi Arabia Laundry Appliances Market
9.8.2. South Africa Laundry Appliances Market
9.8.3. Rest of Middle East & Africa Laundry Appliances Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Whirlpool
10.3.1.1. Key Information
10.3.1.2. Overview
10.3.1.3. Financial (Subject to Data Availability)
10.3.1.4. Product Summary
10.3.1.5. Recent Developments
10.3.2. Alliance Laundry Systems LLC
10.3.3. Videocon Industries Limited
10.3.4. Robert Bosch GmbH
10.3.5. Toshiba Corporation
10.3.6. Candy Hoover Group S.p.A.
10.3.7. Sharp Corporation
10.3.8. Electrolux AB
10.3.9. GD Midea Holding Co. Ltd.
10.3.10. Samsung
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
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Critical elements of methodology employed for all our studies include:
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.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
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:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
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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