Hotels - Zimbabwe | Statista Market Forecast

Hotels - Zimbabwe

Zimbabwe

Highlights

By 2024, the Zimbabwean Hotels market is forecasted to reach a revenue of US$104.80m in the country.
This is expected to grow annually at a rate of 46.68%, resulting in a projected market volume of US$711.90m by 2029.
The number of users in the Hotels market is also expected to increase to 1.28m users by 2029.
In 2024, the user penetration rate is projected to be 4.5%, which is expected to rise to 6.8% by 2029.
The average revenue per user (ARPU) is projected to be US$135.90.
Moreover, it is expected that by 2029, 70% of the total revenue in the Zimbabwean Hotels market will be generated through online sales.
In comparison to the global market, United States is expected to generate the highest revenue of US$111bn in 2024.
Zimbabwe's hotel industry is experiencing a resurgence in investment and infrastructure development, fueled by the country's growing tourism sector.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Hotels market in Zimbabwe is experiencing a notable shift in consumer preferences, market trends, and local special circumstances, all influenced by underlying macroeconomic factors.

Customer preferences: Travelers in Zimbabwe are increasingly seeking unique and authentic experiences, leading to a rise in demand for boutique hotels and lodges that offer a more personalized stay. Tourists are also showing a preference for eco-friendly and sustainable accommodation options, aligning with global trends towards responsible tourism.

Trends in the market: One significant trend in the Zimbabwean Hotels market is the growing popularity of luxury safari lodges, driven by the country's rich wildlife and natural attractions. These lodges offer high-end amenities in the heart of national parks, providing guests with exclusive access to wildlife viewing and conservation activities. Additionally, the rise of digital platforms and online booking systems has made it easier for travelers to discover and book accommodation in Zimbabwe, contributing to the market's growth.

Local special circumstances: Zimbabwe's unique blend of cultural heritage, diverse landscapes, and warm hospitality sets it apart as a desirable tourist destination. The country's renowned national parks, such as Hwange and Mana Pools, attract nature enthusiasts and wildlife lovers from around the world. Furthermore, Zimbabwe's vibrant arts and music scene, along with its rich history, add to the appeal for travelers seeking a multifaceted experience.

Underlying macroeconomic factors: The Hotels market in Zimbabwe is influenced by various macroeconomic factors, including currency fluctuations, political stability, and infrastructure development. The country's efforts to stabilize its economy and attract foreign investment play a crucial role in shaping the hospitality industry. Additionally, government policies and regulations regarding tourism, such as visa requirements and taxation, impact the overall business environment for hotels in Zimbabwe.

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.