Hotels - Philippines

Philippines

Highlights

The Hotels market in the Philippines is poised to generate impressive revenue figures in the years ahead.
By 2024, revenue in this sector is projected to reach US$1.89bn, with an expected annual growth rate (CAGR 2024-2029) of 5.75%.
This growth trajectory is expected to result in a market volume of US$2.50bn by 2029.
Additionally, the number of users is projected to increase to 22.33m users by 2029, with a user penetration rate of 11.1% in 2024, which is expected to increase to 17.5% by 2029.
Moreover, the average revenue per user (ARPU) is expected to be US$143.50.
It is also noteworthy that in the Philippines' Hotels market, 73% of total revenue is expected to be generated through online sales by 2029.
Finally, in terms of global comparison, it is interesting to note that United States is expected to generate the most revenue in this sector, with US$111bn projected for 2024.
The hotel market in the Philippines is experiencing a shift towards sustainable tourism practices and eco-friendly accommodations.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Hotels market in Philippines has been experiencing significant growth and development in recent years.

Customer preferences: Travelers in Philippines are increasingly seeking unique and personalized experiences when choosing their accommodations. This has led to a rise in demand for boutique hotels and eco-friendly resorts that offer a more authentic and sustainable stay. Additionally, with the growing influence of social media, customers are placing more importance on aesthetically pleasing hotels that are Instagram-worthy.

Trends in the market: One notable trend in the Hotels market in Philippines is the increasing popularity of staycations among local residents. With hectic lifestyles and limited travel options due to the pandemic, many Filipinos are opting to spend their vacations at local hotels and resorts. This trend has led to a boost in the domestic tourism sector and has encouraged hotels to offer attractive staycation packages to cater to this growing market.

Local special circumstances: The archipelagic nature of Philippines presents a unique challenge for the Hotels market. With over 7,000 islands, hotel chains and resorts must carefully consider their locations and accessibility to key tourist destinations. This has led to the development of hotels in both popular tourist spots as well as off-the-beaten-path locations to attract a diverse range of travelers.

Underlying macroeconomic factors: The economic growth in Philippines has contributed to the expansion of the Hotels market. With a rising middle class and increasing disposable income, more Filipinos are able to afford travel and accommodations, driving up demand for hotels across the country. Additionally, government initiatives to promote tourism and infrastructure development have further supported the growth of the Hotels market in Philippines.

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and sales channels of hotels.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on a specific rationale for each market. As a basis for evaluating markets, we use financial reports, the Global Consumer Survey, third-party studies and reports, data from industry associations (e.g., UNWTO), and price data of major players in respective markets. To estimate the number of users and bookings, we furthermore use data from the Statista Consumer Insigths Global survey. In addition, we use relevant key market indicators and data from country-specific associations, such as country-related GDP, demographic data (e.g., population), tourism spending, consumer spending, internet penetration, and device penetration. 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, ARIMA, which allows time series forecasts, accounting for stationarity of data and enabling short-term estimates. Additionally, simple linear regression, Holt-Winters forecast, and exponential trend smoothing methods are applied. A k-means cluster analysis allows for the estimation of similar countries. The main drivers are tourism GDP per capita and respective price indices.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change.