Smart Appliances - Eastern Asia

  • Eastern Asia
  • Revenue in the Smart Appliances market is projected to reach US$24.7bn in 2024.
  • Revenue is expected to show an annual growth rate (CAGR 2024-2028) of 12.11%, resulting in a projected market volume of US$39.1bn by 2028.
  • In the Smart Appliances market, the number of active households is expected to amount to 276.4m users by 2028.
  • Household penetration will be 15.7% in 2024 and is expected to hit 47.8% by 2028.
  • The average revenue per installed Smart Home currently is expected to amount to US$277.20.
 
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Analyst Opinion

The Smart Appliances market in Eastern Asia has experienced significant growth in recent years, driven by changing customer preferences, emerging trends, and local special circumstances. Customer preferences in Eastern Asia have shifted towards smart appliances due to their convenience, energy efficiency, and connectivity features.

Consumers are increasingly seeking appliances that can be controlled remotely through smartphones or voice assistants, allowing them to manage their homes more efficiently. Additionally, the growing awareness of environmental issues has led to an increased demand for energy-saving appliances, further fueling the adoption of smart appliances in the region. Trends in the market indicate that smart appliances are becoming more affordable and accessible to a wider range of consumers in Eastern Asia.

As technology advances and production costs decrease, the prices of smart appliances have become more competitive, making them more accessible to the mass market. This trend has been further accelerated by the entry of new players in the market, increasing competition and driving down prices. As a result, smart appliances are no longer seen as luxury items but rather as essential household appliances.

Local special circumstances in Eastern Asia have also contributed to the growth of the smart appliances market. The region has a high population density and urbanization rate, with many people living in small apartments or condominiums. In such compact living spaces, smart appliances offer practical solutions by optimizing space and providing multifunctional features.

For example, smart refrigerators with adjustable shelves and temperature control can maximize storage capacity, while smart washing machines with compact designs can fit into small laundry areas. Underlying macroeconomic factors have also played a role in the development of the smart appliances market in Eastern Asia. The region has experienced rapid economic growth, leading to an increase in disposable income and purchasing power.

As consumers become more affluent, they are willing to invest in high-quality appliances that offer convenience and efficiency. Moreover, government initiatives and incentives to promote energy conservation and sustainable living have further encouraged the adoption of smart appliances. In conclusion, the Smart Appliances market in Eastern Asia is experiencing growth due to changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors.

As consumers increasingly prioritize convenience, energy efficiency, and connectivity, the demand for smart appliances is expected to continue rising in the region.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on the sales of smart home products, excluding taxes.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on a specific rationale for each market category. As a basis for evaluating markets, we use the Statista Global Consumer Survey, market data from independent databases and third-party sources, and Statista interviews with market experts. In addition, we use relevant key market indicators and data from country-specific associations, such as household internet penetration and consumer spending for households. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited for forecasting innovative products due to the non-linear growth of technology adoption. The main drivers are GDP/capita, level of digitization, and consumer attitudes toward smart home integration.

Additional notes:

The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. The market is updated once a year, in case market dynamics change we do more frequent updates.

Overview

  • Revenue
  • Key Players
  • Product Types
  • Global Comparison
  • Analyst Opinion
  • Methodology
  • Key Market Indicators
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