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Package Holidays - Singapore

Singapore

Highlights

Singapore is expected to witness significant growth in the Package Holidays market.
The revenue in this sector is projected to reach US$1.64bn by 2024, with an anticipated annual growth rate (CAGR 2024-2029) of 3.70%.
This growth rate will result in a projected market volume of US$1.97bn by 2029.
The number of users in this market is expected to amount to 1.62m users by 2029.
The user penetration rate is projected to increase from 22.7% in 2024 to 26.1% by 2029.
The average revenue per user (ARPU) is expected to be US$1.19k.
Online sales are projected to generate 85% of total revenue by 2029.
In comparison to other countries, China is expected to generate the highest revenue in the Package Holidays market, with a projected revenue of US$49bn in 2024.
Singaporeans are increasingly seeking unique experiences and personalized itineraries in their package holidays.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Package Holidays market in Singapore has been experiencing significant growth and development in recent years.

Customer preferences: Customers in Singapore are increasingly looking for convenience and hassle-free travel experiences, which has led to a rise in the demand for package holidays. The all-inclusive nature of package holidays, which typically include flights, accommodation, and activities, appeals to busy professionals and families looking for a seamless vacation experience.

Trends in the market: One notable trend in the Package Holidays market in Singapore is the growing popularity of curated and experiential packages. Travelers are seeking unique and personalized experiences that go beyond traditional sightseeing tours, leading to an increase in themed packages such as culinary tours, wellness retreats, and eco-friendly holidays. This trend reflects a shift towards more meaningful and immersive travel experiences among Singaporean tourists.

Local special circumstances: Singapore's strategic location in Southeast Asia makes it a hub for travel to various destinations in the region. The country's well-connected airport and efficient transportation infrastructure make it easy for travelers to access a wide range of package holiday options, from beach getaways in Thailand to cultural tours in Vietnam. Additionally, the multicultural nature of Singapore's population has influenced the diversity of package holidays available, catering to different preferences and interests.

Underlying macroeconomic factors: The strong economy and high levels of disposable income in Singapore have contributed to the growth of the Package Holidays market. As more Singaporeans have the financial means to travel, there is a greater willingness to spend on premium package holidays that offer luxury accommodations and exclusive experiences. Additionally, the government's efforts to promote tourism and position Singapore as a top travel destination have further fueled the demand for package holidays among both domestic and international tourists.

Data coverage:

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

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.