HKUST and Wisers Launch Hong Kong’s First Forward-looking Tourism Index Supporting Tourism Recovery with AI-Powered Predictive Model

The School of Business and Management of The Hong Kong University of Science and Technology (HKUST Business School) today launched the Wisers-HKUST Tourism Index (Tourism Index) in collaboration with Wisers Information Limited (Wisers) in support of Hong Kong’s tourism growth following the resumption of normal travel between Hong Kong and the Mainland. As Hong Kong’s first forward-looking tourism index leveraging artificial intelligence (AI)-powered forecasts, the project will enable industry stakeholders to better gauge near-term tourism outlook for pre-emptive policy and business planning, thereby contributing to the tourism industry’s long-term development.

With a view to supporting forward-looking strategy development and planning by the industry and relevant agencies, the Tourism Index, a joint project between the School’s Center for Business and Social Analytics (CBSA) and Wisers’ Wisers AI, offers forecasts of key tourism metrics based on a predictive model of mainlanders’ intentions in traveling to Hong Kong. The model was constructed using leading-edge AI technologies, such as natural language processing and machine learning, to analyze over 10 million data points[1] from social media platforms, online travel agencies, and travel forums in Mainland China.

The tourism industry faces a challenge in business planning, as key tourism statistics are available with a lag time. For instance, data for January is only accessible in March.  To help address this issue, the Tourism Index provides forecasted values for crucial tourism metrics such as the overall tourism sector outlook, mainland visitors' arrivals, hotel occupancy, and hotel average daily rate. This forward-looking indicator offers a glimpse of the near-term sector outlook, and its forecast values for the current month and the next two months[2] are publicly accessible.

To produce its forecasts, updated on the 10th each month, the Index makes reference to historical tourism statistics and over 20 travel-related influencing factors, including travel desire and sentiments captured from analyzing social/online media postings.

Senior Associate Dean of HKUST Business School and Director of CBSA Professor HUI Kai-Lung said, “Accounting for nearly 80% of visitor arrivals to Hong Kong, mainland visitors hold key to the revival of Hong Kong’s pandemic-hit travel sector. Working at the confluence of business and technology, our research team has put together a set of forward-looking indices showing near-term trends of key tourism metrics to support government agencies and the industry in devising pre-emptive tourism policies. Through this project with practical applications for the tourism sector, we also hope to demonstrate the potential of the fast-growing field of data analytics, and promote the wider use of big data technologies in the business community and beyond.”

CEO of Wisers and Advisor of CBSA Ms. Denise CHE explained, “Powered by Wisers’ extensive Chinese media database and automatic data processing platform, the predictive model underlying the Tourism Index analyzes massive volumes of text data collected by WisersOne from digital platforms frequently used by Chinese travelers, providing a systematic understanding of factors impacting Hong Kong’s tourism arrivals.”

Adjunct Associate Professor of HKUST Business School and Advisor of CBSA Dr. HE Chao noted, “Tourism is one of the four pillar industries in Hong Kong. To help the industry better respond to the fast-changing environment, we have constructed a series of predictive tourism indices. The Wisers-HKUST Tourism Index leverages big data text analytics for the first time to forecast Hong Kong tourism activity levels, overcoming the limitations of traditional surveys' limited insights and the delays in industry statistics.”

Commenting on the Tourism Index, Hong Kong Hotels Association (HKHA) Chairman, Mr. Peter WONG Chak-fung, said, “Marking a significant milestone for the tourism industry, this initiative underscores HKUST's and Wisers' dedication to innovation and the utilization of big data to generate crucial tourism indicators for economic and tourism recovery. HKHA understands the importance of accurate and insightful tourism indicators that can aid hotel operators in making informed decisions.  We eagerly anticipate working together with two organizations to contribute to the sustainable growth and development of Hong Kong's hotel sector as well as smart city transformation.”

Wisers-HKUST Tourism Index comprises the Composite Index, and its three component indices, namely Visitor Arrivals Index, Hotel Occupancy Index, and Hotel Average Daily Rate Index, which are the weighted average of the Composite Index, with weights of 50%, 25%, and 25% respectively. The Index is available for viewing on the CBSA website at:

https://tourismindex.hkust.edu.hk/

Appendix:

Guide to using the Wisers-HKUST Tourism Index

• Composite Index is a leading indicator for overall level of tourism interest in Hong Kong. It is a weighted average of its three components, namely Visitor Arrivals Index, Hotel Occupancy Index, and Hotel Average Daily Rate Index.
• Component indices
  • Visitor Arrivals Index forecasts the mainland visitor arrivals to Hong Kong
  • Hotel Occupancy Index forecasts the hotel occupancy in Hong Kong
  • Hotel Average Daily Rate Index forecasts the hotel average daily rate in Hong Kong
• The Composite Index and the three component indices are expressed as a percentage of a base value, which is the value of the 2018 average. The index value for the average monthly actual value recorded in 2018 is set at 100. For example, a Visitor Arrivals Index reading of 120 means that the number of visitor arrivals is forecast to be 120% of the average monthly actual value in 2018.

The blue/yellow lines on the charts on the Tourism Index website track the index values projected by the Tourism Index. Calculated from the publicly available data on HKTB PartnerNet website, the red lines track the actual index values.

[1] A data point refers to a post made on social media, online travel agencies, and travel forums

[2] The Tourism Index’s forecasts for the period from Jan 2018 and Mar 2023 had an error rate as low as 4%, according to a study by a research team of CBSA and Wisers AI