Yanolja Research

Trend. Q4 2024 Trends in Lodging Industry Performance by Property Type in Q4 2024 Compared to Q4 2023 Performance by Property Type in Q4 2024 Compared to Q3 2024 Lodging Business Outlook Index of Q1 2025 Changes in Operational Status by Property Type 1. Hotel Hotel Operating Status by Region and Star Rating 2. Motel Motel Operating Status by Region 3. Pension Pension Operating Status by Region 4. Vacation Rental Vacation Rental Operating Status by Region Issue. The Role of Regional Airports in Promoting Inbound Tourism Inbound Tourist Demand Comparison by Continent Inbound Tourist Demand of Key Asian Countries The Possibilities of Regional Airport Revitalization Strategies: Insights from the Taiwan Case Yanolja Research Korean Lodging Industry Trends Report for Q4 2024

🌏 South Korea’s Path to Becoming a Global Tourism Powerhouse To thrive in the post-pandemic travel era, South Korea is charting a bold new course—one that blends smart branding, strategic partnerships, and deep cultural understanding. Here's a quick look at the nation's forward-thinking approach to elevating its global tourism profile. 🇰🇷 A Unified National Brand is Key A strong, government-led tourism brand is essential to distinguish Korea from competitors. Just like top-performing companies, leading tourism countries build identity through targeted storytelling and market-specific strategies . The strategy: Align ministries, local governments, and private players under a single, consistent vision. 📌 Market-Specific Targeting Drives Results Rather than a one-size-fits-all model, Korea aims to analyze and tailor offerings to key markets .  Learnings from global peers: 🇦🇺  Australia’s China Strategy included local partnerships and staff training. 🇯🇵 Japan's appr...

Forecasting South Korea's Inbound Tourism Demand Using an AI-Based LSTM Model South Korea’s inbound tourism outlook for 2025 is being shaped by cutting-edge AI technology, marking a new era in tourism forecasting. AI-Powered Forecasting: The Game Changer Yanolja Research developed an advanced AI model based on LSTM (Long Short-Term Memory) deep learning technology, specially designed to analyze time-series data and capture long-term trends in tourism demand. This model integrates diverse data sources including global mobility patterns, economic indicators, and social media trends to deliver highly accurate predictions. The model’s precision is proven by its recent forecast accuracy: it predicted 16.08 million visitors for Nov 2023–Oct 2024, closely matching the actual 15.88 million with only a 1.3% error margin. What the AI Model Predicts for 2025 Approximately 18.73 million foreign tourists are expected to visit South Korea in 2025, a 7% increase over the 2019 pre-pandemic peak. T...