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Wisers-HKUST Tourism Index

Developed in collaboration with Wisers Information Limited, the Tourism Index is a predictive index of tourism demand derived from social big data and powered by the latest natural language processing technologies and advanced statistical models.

The Wisers-HKUST Tourism Index is an advanced forecasting tool that combines big data analytics, natural language processing (NLP), and statistical modeling to predict tourism trends in Hong Kong. By systematically analyzing 20+ travel-related factors, social media sentiment, and historical industry data, the index provides reliable forecasts of visitor arrivals, hotel occupancy, and average daily rates to support strategic decision-making across the tourism sector.


Key Features

  • Composite Forecasting Model: Integrates three core indicators with scientific weighting:

    • Mainland Visitor Arrivals (50%)

    • Hotel Occupancy Rates (25%)

    • Hotel Average Daily Rates (25%)

      2018 baseline = 100

  • High Predictive Accuracy: Achieves 96% forecast precision with mean absolute error as low as 4%

  • Comprehensive Data Integration: Processes 10+ million data points from periodic collections of:

    • Travel forums and review platforms

    • Social media discussions

    • Online travel agency metrics

  • Cutting-Edge Methodology: Combines Wisers AI's NLP technology with HKUST's statistical modeling


Strategic Value

As tourism contributes ~4.5% of Hong Kong's GDP, this index enables:

  • Hospitality Sector: Data-driven capacity and pricing decisions

  • Retail & Attractions: Strategic planning aligned with tourist inflows

  • Policy Makers: Evidence-based sector monitoring and infrastructure planning

  • Investors: Risk assessment and market opportunity evaluation


Methodology

  • Periodic Data Collection: Aggregates and cleanses tourism-related discourse from:

    • Chinese-language social media

    • Travel platforms and forums

    • Industry reports and datasets

  • Sentiment Analysis: Wisers' NLP system identifies and categorizes:

    • Travel intent signals

    • Accommodation preferences

    • Destination sentiment

  • Predictive Modeling: HKUST's machine learning algorithms:

    • Correlate processed sentiment with historical tourism data

    • Generate forward-looking indicators with validated accuracy


Index Applications

  • Market Analysis: Identify emerging tourism trends

  • Operational Planning: Optimize resource allocation

  • Policy Development: Monitor sector performance

  • Investment Decisions: Assess market potential


Access the Data: Full methodology and forecasts available at: https://tourismindex.hkust.edu.hk

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Center for Business and Social Analytics​​

Rm 6061, Lee Shau Kee Business Building

The Hong Kong University of Science and Technology
Clear Water Bay, Kowloon, Hong Kong

cbsa [at] ust [dot] hk   |   (852) 3469 2637

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