Hotels - Cyprus

  • Cyprus
  • By 2024, the projected revenue in the Hotels market in Cyprus is expected to reach US$76.03m.
  • It is also expected to manifest an annual growth rate (CAGR 2024-2028) of 8.20%, which will result in a market volume of US$104.20m by 2028.
  • Furthermore, the Hotels market in Cyprus is expected to have 260.40k users users by 2028.
  • In 2024, user penetration is 17.4% and is anticipated to hit 20.1% by 2028.
  • The average revenue per user (ARPU) is expected to be US$345.50.
  • By 2028, online sales will contribute to 90% of the total revenue.
  • It is worth noting that, in comparison to other countries, United States is projected to generate the most revenue in the Hotels market with US$110,500m in 2024.
  • Cyprus’ hotel market is experiencing a shift towards luxury and boutique accommodations to cater to the high-end tourism market.

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

 
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Analyst Opinion

The Hotels market in Cyprus reflects a dynamic and evolving industry that is influenced by various factors.

Customer preferences:
Customers in Cyprus are increasingly looking for unique and personalized experiences when choosing hotels. They seek accommodations that offer cultural immersion, authentic local cuisine, and eco-friendly practices. This trend aligns with the global shift towards experiential travel, where tourists prioritize memorable experiences over traditional amenities.

Trends in the market:
In Cyprus, there is a growing trend towards boutique hotels and eco-friendly resorts. These establishments cater to the demand for sustainable tourism practices and offer a more intimate setting for guests. Additionally, the rise of digital platforms has revolutionized the way hotels market their services and engage with customers. Online booking platforms and social media play a crucial role in reaching a wider audience and driving bookings.

Local special circumstances:
Cyprus benefits from its strategic location at the crossroads of Europe, Africa, and Asia, attracting a diverse range of tourists. The island's rich history, stunning beaches, and vibrant culture make it a popular destination for both leisure and business travelers. The seasonal nature of tourism in Cyprus also impacts the hotel market, with peak seasons seeing high demand for accommodations.

Underlying macroeconomic factors:
The Hotels market in Cyprus is influenced by macroeconomic factors such as exchange rates, government policies, and global economic conditions. Fluctuations in currency exchange rates can impact tourism flows and affect hotel revenues. Government initiatives to promote tourism and investment in infrastructure play a crucial role in driving the growth of the hotel industry. Additionally, global economic trends and geopolitical events can have ripple effects on tourism in Cyprus, influencing hotel occupancy rates and overall market performance.

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.

Overview

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Hotel Star Rating
  • Methodology
  • Key Market Indicators
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