Market Insights Mobility Travel & Tourism

Hotels - Indonesia

Indonesia

Indonesia is projected to reach a revenue of €4.60bn in the Hotels market by 2024.
An annual growth rate of 3.75% is expected between 2024 and 2028, resulting in a projected market volume of €5.33bn by 2028.
By 2028, the number of users in the Hotels market is expected to amount to 30.88m users.
The user penetration rate is anticipated to increase from 9.9% in 2024 to 10.7% by 2028.
The average revenue per user (ARPU) is expected to be €166.50.
Online sales are expected to generate 83% of the total revenue by 2028 in the Hotels market.
It is worth noting that in the Hotels market, United States is expected to generate the most revenue globally, amounting to €101,000m in 2024.
Indonesia's hotel market is experiencing a rise in demand due to the country's growing tourism industry and diverse cultural offerings.

Key regions: Singapore, Indonesia, India, United States, Europe

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Analyst Opinion

The Hotels market in Indonesia is experiencing significant growth and development.

Customer preferences: Travelers in Indonesia are increasingly looking for unique and authentic experiences when choosing their accommodation. They prefer hotels that offer cultural immersion, eco-friendly practices, and personalized services. Additionally, there is a rising demand for budget-friendly options among domestic tourists.

Trends in the market: One of the noticeable trends in the Indonesian hotel market is the rapid expansion of international hotel chains in major cities and tourist destinations. This trend is driven by the growing number of international visitors and the desire to cater to their specific needs and preferences. Moreover, there is a shift towards technology integration in hotels, with many establishments adopting online booking platforms, mobile check-ins, and smart room features to enhance the overall guest experience.

Local special circumstances: Indonesia's diverse landscape and rich cultural heritage make it a popular tourist destination, attracting travelers from all over the world. The country's archipelago offers a wide range of attractions, from pristine beaches and lush jungles to ancient temples and vibrant cities. This diversity presents a unique opportunity for hoteliers to cater to different types of travelers and offer a variety of accommodations to suit their preferences.

Underlying macroeconomic factors: The steady growth of Indonesia's economy and the increasing disposable income of its population have contributed to the expansion of the Hotels market. The government's efforts to promote tourism and improve infrastructure have also played a significant role in attracting both domestic and international visitors to the country. Additionally, the rise of digital platforms and online travel agencies has made it easier for hotels to reach a wider audience and increase their bookings.

Methodology

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.